Sensors

2022

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27 pages, 3372 KiB

Open AccessReview

Advances in Therapeutic Monitoring of Lithium in the Management of Bipolar Disorder

by Mahsa Sheikh, Meha Qassem, Iasonas F. Triantis and Panicos A. Kyriacou

Sensors 2022, 22(3), 736; https://doi.org/10.3390/s22030736 - 19 Jan 2022

Cited by 21 | Viewed by 8446

Abstract

Since the mid-20th century, lithium continues to be prescribed as a first-line mood stabilizer for the management of bipolar disorder (BD). However, lithium has a very narrow therapeutic index, and it is crucial to carefully monitor lithium plasma levels as concentrations greater than [...] Read more.

Since the mid-20th century, lithium continues to be prescribed as a first-line mood stabilizer for the management of bipolar disorder (BD). However, lithium has a very narrow therapeutic index, and it is crucial to carefully monitor lithium plasma levels as concentrations greater than 1.2 mmol/L are potentially toxic and can be fatal. The quantification of lithium in clinical laboratories is performed by atomic absorption spectrometry, flame emission photometry, or conventional ion-selective electrodes. All these techniques are cumbersome and require frequent blood tests with consequent discomfort which results in patients evading treatment. Furthermore, the current techniques for lithium monitoring require highly qualified personnel and expensive equipment; hence, it is crucial to develop low-cost and easy-to-use devices for decentralized monitoring of lithium. The current paper seeks to review the pertinent literature rigorously and critically with a focus on different lithium-monitoring techniques which could lead towards the development of automatic and point-of-care analytical devices for lithium determination. Full article

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2021

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15 pages, 9697 KiB

Open AccessArticle

Kinect V2-Based Gait Analysis for Children with Cerebral Palsy: Validity and Reliability of Spatial Margin of Stability and Spatiotemporal Variables

by Yunru Ma, Kumar Mithraratne, Nichola Wilson, Yanxin Zhang and Xiangbin Wang

Sensors 2021, 21(6), 2104; https://doi.org/10.3390/s21062104 - 17 Mar 2021

Cited by 20 | Viewed by 4309

Abstract

Children with cerebral palsy (CP) have high risks of falling. It is necessary to evaluate gait stability for children with CP. In comparison to traditional motion capture techniques, the Kinect has the potential to be utilised as a cost-effective gait stability assessment tool, [...] Read more.

Children with cerebral palsy (CP) have high risks of falling. It is necessary to evaluate gait stability for children with CP. In comparison to traditional motion capture techniques, the Kinect has the potential to be utilised as a cost-effective gait stability assessment tool, ensuring frequent and uninterrupted gait monitoring. To evaluate the validity and reliability of this measurement, in this study, ten children with CP performed two testing sessions, of which gait data were recorded by a Kinect V2 sensor and a referential Motion Analysis system. The margin of stability (MOS) and gait spatiotemporal metrics were examined. For the spatiotemporal parameters, intraclass correlation coefficient (ICC_2,k) values were from 0.83 to 0.99 between two devices and from 0.78 to 0.88 between two testing sessions. For the MOS outcomes, ICC_2,k values ranged from 0.42 to 0.99 between two devices and 0.28 to 0.69 between two test sessions. The Kinect V2 was able to provide valid and reliable spatiotemporal gait parameters, and it could also offer accurate outcome measures for the minimum MOS. The reliability of the Kinect V2 when assessing time-specific MOS variables was limited. The Kinect V2 shows the potential to be used as a cost-effective tool for CP gait stability assessment. Full article

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2019

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19 pages, 5343 KiB

Open AccessArticle

Dynamic Hand Gesture Recognition Using 3DCNN and LSTM with FSM Context-Aware Model

by Noorkholis Luthfil Hakim, Timothy K. Shih, Sandeli Priyanwada Kasthuri Arachchi, Wisnu Aditya, Yi-Cheng Chen and Chih-Yang Lin

Sensors 2019, 19(24), 5429; https://doi.org/10.3390/s19245429 - 9 Dec 2019

Cited by 51 | Viewed by 11637

Abstract

With the recent growth of Smart TV technology, the demand for unique and beneficial applications motivates the study of a unique gesture-based system for a smart TV-like environment. Combining movie recommendation, social media platform, call a friend application, weather updates, chatting app, and [...] Read more.

With the recent growth of Smart TV technology, the demand for unique and beneficial applications motivates the study of a unique gesture-based system for a smart TV-like environment. Combining movie recommendation, social media platform, call a friend application, weather updates, chatting app, and tourism platform into a single system regulated by natural-like gesture controller is proposed to allow the ease of use and natural interaction. Gesture recognition problem solving was designed through 24 gestures of 13 static and 11 dynamic gestures that suit to the environment. Dataset of a sequence of RGB and depth images were collected, preprocessed, and trained in the proposed deep learning architecture. Combination of three-dimensional Convolutional Neural Network (3DCNN) followed by Long Short-Term Memory (LSTM) model was used to extract the spatio-temporal features. At the end of the classification, Finite State Machine (FSM) communicates the model to control the class decision results based on application context. The result suggested the combination data of depth and RGB to hold 97.8% of accuracy rate on eight selected gestures, while the FSM has improved the recognition rate from 89% to 91% in a real-time performance. Full article

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24 pages, 6040 KiB

Open AccessArticle

Multi-Sensor Data Fusion in A Real-Time Support System for On-Duty Firefighters

by Van Thanh Pham, Quang Bon Le, Duc Anh Nguyen, Nhu Dinh Dang, Huu Tue Huynh and Duc Tan Tran

Sensors 2019, 19(21), 4746; https://doi.org/10.3390/s19214746 - 1 Nov 2019

Cited by 24 | Viewed by 5478

Abstract

While working on fire ground, firefighters risk their well-being in a state where any incident might cause not only injuries, but also fatality. They may be incapacitated by unpredicted falls due to floor cracks, holes, structure failure, gas explosion, exposure to toxic gases, [...] Read more.

While working on fire ground, firefighters risk their well-being in a state where any incident might cause not only injuries, but also fatality. They may be incapacitated by unpredicted falls due to floor cracks, holes, structure failure, gas explosion, exposure to toxic gases, or being stuck in narrow path, etc. Having acknowledged this need, in this study, we focus on developing an efficient portable system to detect firefighter’s falls, loss of physical performance, and alert high CO level by using a microcontroller carried by a firefighter with data fusion from a 3-DOF (degrees of freedom) accelerometer, 3-DOF gyroscope, 3-DOF magnetometer, barometer, and a MQ7 sensor using our proposed fall detection, loss of physical performance detection, and CO monitoring algorithms. By the combination of five sensors and highly efficient data fusion algorithms to observe the fall event, loss of physical performance, and detect high CO level, we can distinguish among falling, loss of physical performance, and the other on-duty activities (ODAs) such as standing, walking, running, jogging, crawling, climbing up/down stairs, and moving up/down in elevators. Signals from these sensors are sent to the microcontroller to detect fall, loss of physical performance, and alert high CO level. The proposed algorithms can achieve 100% of accuracy, specificity, and sensitivity in our experimental datasets and 97.96%, 100%, and 95.89% in public datasets in distinguishing between falls and ODAs activities, respectively. Furthermore, the proposed algorithm perfectly distinguishes between loss of physical performance and up/down movement in the elevator based on barometric data fusion. If a firefighter is unconscious following the fall or loss of physical performance, an alert message will be sent to their incident commander (IC) via the nRF224L01 module. Full article

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12 pages, 1557 KiB

Open AccessArticle

Effects of Frequency Filtering on Intensity and Noise in Accelerometer-Based Physical Activity Measurements

by Jonatan Fridolfsson, Mats Börjesson, Christoph Buck, Örjan Ekblom, Elin Ekblom-Bak, Monica Hunsberger, Lauren Lissner and Daniel Arvidsson

Sensors 2019, 19(9), 2186; https://doi.org/10.3390/s19092186 - 11 May 2019

Cited by 49 | Viewed by 8851

Abstract

In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect [...] Read more.

In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect of wider frequency filters on measurements of PA, sedentary behavior (SED), and capturing of noise. Apart from the standard AG band-pass filter (0.29–1.63 Hz), modified filters with low-pass component cutoffs at 4 Hz, 10 Hz, or removed were analyzed. Calibrations against energy expenditure were performed with lab data from children and adults to generate filter-specific intensity cut-points. Free-living accelerometer data from children and adults were processed using the different filters and intensity cut-points. There was a contribution of acceleration related to PA at frequencies up to 10 Hz. The contribution was more pronounced at moderate and vigorous PA levels, although additional acceleration also occurred at SED. The classification discrepancy between AG and the wider filters was small at SED (1–2%) but very large at the highest intensities (>90%). The present study suggests an optimal low-pass frequency filter with a cutoff at 10 Hz to include all acceleration relevant to PA with minimal effect of noise. Full article

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2018

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19 pages, 4348 KiB

Open AccessArticle

Conductive Thread-Based Textile Sensor for Continuous Perspiration Level Monitoring

by Ji Jia, Chengtian Xu, Shijia Pan, Stephen Xia, Peter Wei, Hae Young Noh, Pei Zhang and Xiaofan Jiang

Sensors 2018, 18(11), 3775; https://doi.org/10.3390/s18113775 - 5 Nov 2018

Cited by 53 | Viewed by 8758

Abstract

Individual perspiration level indicates a person’s physical status as well as their comfort level. Therefore, continuous perspiration level measurement enables people to monitor these conditions for applications including fitness assessment, athlete physical status monitoring, and patient/elderly care. Prior work on perspiration (sweat) sensing [...] Read more.

Individual perspiration level indicates a person’s physical status as well as their comfort level. Therefore, continuous perspiration level measurement enables people to monitor these conditions for applications including fitness assessment, athlete physical status monitoring, and patient/elderly care. Prior work on perspiration (sweat) sensing required the user either to be static or to wear the adhesive sensor directly on the skin, which limits users’ mobility and comfort. In this paper, we present a novel conductive thread-based textile sensor that measures an individual’s on-cloth sweat quantity. The sensor consists of three conductive threads. Each conductive thread is surrounded by a braided cotton cover. An additional braided cotton cover is placed outside the three conductive threads, holding them in a position that is stable for measurement. the sensor can be embedded at various locations on a person’s clothing. When the person sweats, the cotton braids absorb the sweat and change the conductivity (resistance) between conductive threads. We used a voltage dividing circuit to measure this resistance as the sensor output (DC). We then conducted a sensor calibration to map this measured voltage to the quantity of electrolyte solution (with the same density as sweat) applied to the sensor. We used this sensor to measure individuals’ perspiration quantity and infer their perceived perspiration levels. The system is able to limit the average prediction error to 0.4 levels when compared to five pre-defined perceived perspiration levels. Full article

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16 pages, 2905 KiB

Open AccessArticle

Unobtrusive Photoplethysmographic Monitoring Under the Foot Sole while in a Standing Posture

by Seunghyeok Hong and Kwang Suk Park

Sensors 2018, 18(10), 3239; https://doi.org/10.3390/s18103239 - 26 Sep 2018

Cited by 6 | Viewed by 6198

Abstract

Photoplethysmography (PPG) of the foot sole could provide additional health-related information compared with traditional PPG of the finger or wrist. Previously, foot PPG required the procedural binding of a light-emitting diode (LED)-photodetector (PD) pair. We achieved PPG of the foot sole without binding [...] Read more.

Photoplethysmography (PPG) of the foot sole could provide additional health-related information compared with traditional PPG of the finger or wrist. Previously, foot PPG required the procedural binding of a light-emitting diode (LED)-photodetector (PD) pair. We achieved PPG of the foot sole without binding any sensors to the foot while the participant stood in a natural standing position on the testing device. Foot PPG was performed using multiple LED-PD pairs to overcome motion artefacts caused by stabilization. We identified regions of the sole suitable for reliable sensor positioning with optimal LED-PD pairs on the basis of the estimated heart rate (HR) and signal quality index derived by dynamic time warping (wSQI). The first experiment included four participants with direct skin-to-sensor contact, and the results showed a mean HR estimation error of 0.01 beats/min and a wSQI of 0.909. The extended experiment with 53 participants, which involved including a gap between the skin and sensors to consider real-life applications, yielded a mean HR estimation error of 0.638 beats/min and a wSQI of 0.751. Based on the selection ratio of optimal LED-PD pairs, the best region of the sole for PPG was the midfoot, except the medial longitudinal arch. In conclusion, we confirmed that foot PPG using multiple LED-PD pairs is appropriate for HR evaluation and further applications. Full article

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23 pages, 3877 KiB

Open AccessArticle

Automatic Outcome in Manual Dexterity Assessment Using Colour Segmentation and Nearest Neighbour Classifier

by Edwin Daniel Oña, Patricia Sánchez-Herrera, Alicia Cuesta-Gómez, Santiago Martinez, Alberto Jardón and Carlos Balaguer

Sensors 2018, 18(9), 2876; https://doi.org/10.3390/s18092876 - 31 Aug 2018

Cited by 11 | Viewed by 5786

Abstract

Objective assessment of motor function is an important component to evaluating the effectiveness of a rehabilitation process. Such assessments are carried out by clinicians using traditional tests and scales. The Box and Blocks Test (BBT) is one such scale, focusing on manual dexterity [...] Read more.

Objective assessment of motor function is an important component to evaluating the effectiveness of a rehabilitation process. Such assessments are carried out by clinicians using traditional tests and scales. The Box and Blocks Test (BBT) is one such scale, focusing on manual dexterity evaluation. The score is the maximum number of cubes that a person is able to displace during a time window. In a previous paper, an automated version of the Box and Blocks Test using a Microsoft Kinect sensor was presented, and referred to as the Automated Box and Blocks Test (ABBT). In this paper, the feasibility of ABBT as an automated tool for manual dexterity assessment is discussed. An algorithm, based on image segmentation in CIELab colour space and the Nearest Neighbour (NN) rule, was developed to improve the reliability of automatic cube counting. A pilot study was conducted to assess the hand motor function in people with Parkinson’s disease (PD). Three functional assessments were carried out. The success rate in automatic cube counting was studied by comparing the manual (BBT) and the automatic (ABBT) methods. The additional information provided by the ABBT was analysed to discuss its clinical significance. The results show a high correlation between manual (BBT) and automatic (ABBT) scoring. The lowest average success rate in cube counting for ABBT was 92%. Additionally, the ABBT acquires extra information from the cubes’ displacement, such as the average velocity and the time instants in which the cube was detected. The analysis of this information can be related to indicators of health status (coordination and dexterity). The results showed that the ABBT is a useful tool for automating the assessment of unilateral gross manual dexterity, and provides additional information about the user’s performance. Full article

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12 pages, 3205 KiB

Open AccessArticle

Detection of Hemiplegic Walking Using a Wearable Inertia Sensing Device

by Junseok Lee, Sooji Park and Hangsik Shin

Sensors 2018, 18(6), 1736; https://doi.org/10.3390/s18061736 - 28 May 2018

Cited by 16 | Viewed by 4584

Abstract

Hemiplegia is a symptom that is caused by reduced sensory and motor ability on one side of the body due to stroke-related neural defects. Muscular weakness and abnormal sensation that is induced by hemiplegia usually lead to motor impairments, such as difficulty in [...] Read more.

Hemiplegia is a symptom that is caused by reduced sensory and motor ability on one side of the body due to stroke-related neural defects. Muscular weakness and abnormal sensation that is induced by hemiplegia usually lead to motor impairments, such as difficulty in controlling the trunk, unstable balance, and poor walking ability. Therefore, most hemiplegia patients show defective and asymmetric gait pattern. The purpose of this study is to distinguish hemiplegic gait by extracting simple characteristics of acceleration signals that are caused by asymmetry during walking using a wearable system. The devised wearable system was equipped with a three-axis accelerometer and a three-axis gyroscope. We selected 165 candidate features without step detection. A random forest algorithm was used for the classification, and the forward search algorithm was also used for optimal feature selection. The developed system and algorithms were verified clinically in 15 normal subjects and 20 hemiplegia patients that were undergoing stroke treatment, and 26 subject’s data was used for training, including validation, and nine subject’s data used for test. As a result of test set, the accuracy, sensitivity, specificity and positive predictive value were 100.0%, with the two classification attributes of standard deviation of points perpendicular to the axis of line of identity of Poincaré plot of angular velocity around vertical axis and kurtosis of frequency of angular velocity around longitudinal axis. Full article

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16 pages, 1563 KiB

Open AccessArticle

Measuring Gait Quality in Parkinson’s Disease through Real-Time Gait Phase Recognition

by Ilaria Mileti, Marco Germanotta, Enrica Di Sipio, Isabella Imbimbo, Alessandra Pacilli, Carmen Erra, Martina Petracca, Stefano Rossi, Zaccaria Del Prete, Anna Rita Bentivoglio, Luca Padua and Eduardo Palermo

Sensors 2018, 18(3), 919; https://doi.org/10.3390/s18030919 - 20 Mar 2018

Cited by 38 | Viewed by 6900

Abstract

Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, [...] Read more.

Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, were compared. The methods were tested on 26 PD patients, both in OFF and ON levodopa conditions, and 11 healthy subjects, during walking tasks. All subjects were equipped with inertial sensors placed on feet. Force resistive sensors were used to assess reference time sequence of gait phases. Goodness Index (G) was evaluated to assess accuracy in gait phases estimation. A novel synthetic index called Gait Phase Quality Index (GPQI) was proposed for gait quality assessment. Results revealed optimum performance (G < 0.25) for three tested methods and good performance (0.25 < G < 0.70) for one threshold method. The GPQI resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score. Furthermore, in patients with severe gait impairment, GPQI was found higher in OFF than in ON state. Our results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors. Full article

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2017

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6148 KiB

Open AccessArticle

Motor Control Training for the Shoulder with Smart Garments

by Qi Wang, Liesbet De Baets, Annick Timmermans, Wei Chen, Luca Giacolini, Thomas Matheve and Panos Markopoulos

Sensors 2017, 17(7), 1687; https://doi.org/10.3390/s17071687 - 22 Jul 2017

Cited by 20 | Viewed by 12392

Abstract

Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the [...] Read more.

Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the various technological options for posture monitoring, wearable systems offer potential advantages regarding mobility, use in different contexts and sustained tracking in daily life. We describe the design of a smart garment named Zishi to monitor compensatory movements and evaluate its applicability for shoulder motor control training in a clinical setting. Five physiotherapists and eight patients with musculoskeletal shoulder pain participated in the study. The attitudes of patients and therapists towards the system were measured using standardized survey instruments. The results indicate that patients and their therapists consider Zishi a credible aid for rehabilitation and patients expect it will help towards their recovery. The system was perceived as highly usable and patients were motivated to train with the system. Future research efforts on the improvement of the customization of feedback location and modality, and on the evaluation of Zishi as support for motor learning in shoulder patients, should be made. Full article

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16588 KiB

Open AccessReview

Sensor-Based Assistive Devices for Visually-Impaired People: Current Status, Challenges, and Future Directions

by Wafa Elmannai and Khaled Elleithy

Sensors 2017, 17(3), 565; https://doi.org/10.3390/s17030565 - 10 Mar 2017

Cited by 227 | Viewed by 36911

Abstract

The World Health Organization (WHO) reported that there are 285 million visuallyimpaired people worldwide. Among these individuals, there are 39 million who are totally blind. There have been several systems designed to support visually-impaired people and to improve the quality of their lives. [...] Read more.

The World Health Organization (WHO) reported that there are 285 million visuallyimpaired people worldwide. Among these individuals, there are 39 million who are totally blind. There have been several systems designed to support visually-impaired people and to improve the quality of their lives. Unfortunately, most of these systems are limited in their capabilities. In this paper, we present a comparative survey of the wearable and portable assistive devices for visuallyimpaired people in order to show the progress in assistive technology for this group of people. Thus, the contribution of this literature survey is to discuss in detail the most significant devices that are presented in the literature to assist this population and highlight the improvements, advantages, disadvantages, and accuracy. Our aim is to address and present most of the issues of these systems to pave the way for other researchers to design devices that ensure safety and independent mobility to visually-impaired people. Full article

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6744 KiB

Open AccessArticle

Experimental Validation of Depth Cameras for the Parameterization of Functional Balance of Patients in Clinical Tests

by Francisco-Ángel Moreno, José Antonio Merchán-Baeza, Manuel González-Sánchez, Javier González-Jiménez and Antonio I. Cuesta-Vargas

Sensors 2017, 17(2), 424; https://doi.org/10.3390/s17020424 - 22 Feb 2017

Cited by 12 | Viewed by 6037

Abstract

In clinical practice, patients’ balance can be assessed using standard scales. Two of the most validated clinical tests for measuring balance are the Timed Up and Go (TUG) test and the MultiDirectional Reach Test (MDRT). Nowadays, inertial sensors (IS) are employed for kinematic [...] Read more.

In clinical practice, patients’ balance can be assessed using standard scales. Two of the most validated clinical tests for measuring balance are the Timed Up and Go (TUG) test and the MultiDirectional Reach Test (MDRT). Nowadays, inertial sensors (IS) are employed for kinematic analysis of functional tests in the clinical setting, and have become an alternative to expensive, 3D optical motion capture systems. In daily clinical practice, however, IS-based setups are yet cumbersome and inconvenient to apply. Current depth cameras have the potential for such application, presenting many advantages as, for instance, being portable, low-cost and minimally-invasive. This paper aims at experimentally validating to what extent this technology can substitute IS for the parameterization and kinematic analysis of the TUG and the MDRT tests. Twenty healthy young adults were recruited as participants to perform five different balance tests while kinematic data from their movements were measured by both a depth camera and an inertial sensor placed on their trunk. The reliability of the camera’s measurements is examined through the Interclass Correlation Coefficient (ICC), whilst the Pearson Correlation Coefficient (r) is computed to evaluate the correlation between both sensor’s measurements, revealing excellent reliability and strong correlations in most cases. Full article

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5064 KiB

Open AccessArticle

Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone

by Rifat Zaman, Chae Ho Cho, Konrad Hartmann-Vaccarezza, Tra Nguyen Phan, Gwonchan Yoon and Jo Woon Chong

Sensors 2017, 17(2), 358; https://doi.org/10.3390/s17020358 - 12 Feb 2017

Cited by 19 | Viewed by 6920

Abstract

We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained [...] Read more.

We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively. Full article

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2302 KiB

Open AccessReview

A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time

by Zhihua Wang, Zhaochu Yang and Tao Dong

Sensors 2017, 17(2), 341; https://doi.org/10.3390/s17020341 - 10 Feb 2017

Cited by 275 | Viewed by 27719

Abstract

Rapid growth of the aged population has caused an immense increase in the demand for healthcare services. Generally, the elderly are more prone to health problems compared to other age groups. With effective monitoring and alarm systems, the adverse effects of unpredictable events [...] Read more.

Rapid growth of the aged population has caused an immense increase in the demand for healthcare services. Generally, the elderly are more prone to health problems compared to other age groups. With effective monitoring and alarm systems, the adverse effects of unpredictable events such as sudden illnesses, falls, and so on can be ameliorated to some extent. Recently, advances in wearable and sensor technologies have improved the prospects of these service systems for assisting elderly people. In this article, we review state-of-the-art wearable technologies that can be used for elderly care. These technologies are categorized into three types: indoor positioning, activity recognition and real time vital sign monitoring. Positioning is the process of accurate localization and is particularly important for elderly people so that they can be found in a timely manner. Activity recognition not only helps ensure that sudden events (e.g., falls) will raise alarms but also functions as a feasible way to guide people’s activities so that they avoid dangerous behaviors. Since most elderly people suffer from age-related problems, some vital signs that can be monitored comfortably and continuously via existing techniques are also summarized. Finally, we discussed a series of considerations and future trends with regard to the construction of “smart clothing” system. Full article

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10383 KiB

Open AccessArticle

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine

by Haerin Lee, Moonki Jung, Ki-Kwang Lee and Sang Hun Lee

Sensors 2017, 17(2), 299; https://doi.org/10.3390/s17020299 - 6 Feb 2017

Cited by 10 | Viewed by 11963

Abstract

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate [...] Read more.

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human–machine–environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines. Full article

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Open AccessArticle

A Detailed Algorithm for Vital Sign Monitoring of a Stationary/Non-Stationary Human through IR-UWB Radar

by Faheem Khan and Sung Ho Cho

Sensors 2017, 17(2), 290; https://doi.org/10.3390/s17020290 - 4 Feb 2017

Cited by 115 | Viewed by 16030

Abstract

The vital sign monitoring through Impulse Radio Ultra-Wide Band (IR-UWB) radar provides continuous assessment of a patient’s respiration and heart rates in a non-invasive manner. In this paper, IR UWB radar is used for monitoring respiration and the human heart rate. The breathing [...] Read more.

The vital sign monitoring through Impulse Radio Ultra-Wide Band (IR-UWB) radar provides continuous assessment of a patient’s respiration and heart rates in a non-invasive manner. In this paper, IR UWB radar is used for monitoring respiration and the human heart rate. The breathing and heart rate frequencies are extracted from the signal reflected from the human body. A Kalman filter is applied to reduce the measurement noise from the vital signal. An algorithm is presented to separate the heart rate signal from the breathing harmonics. An auto-correlation based technique is applied for detecting random body movements (RBM) during the measurement process. Experiments were performed in different scenarios in order to show the validity of the algorithm. The vital signs were estimated for the signal reflected from the chest, as well as from the back side of the body in different experiments. The results from both scenarios are compared for respiration and heartbeat estimation accuracy. Full article

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Open AccessArticle

Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

by Tan-Hsu Tan, Munkhjargal Gochoo, Yung-Fu Chen, Jin-Jia Hu, John Y. Chiang, Ching-Su Chang, Ming-Huei Lee, Yung-Nian Hsu and Jiin-Chyr Hsu

Sensors 2017, 17(1), 202; https://doi.org/10.3390/s17010202 - 21 Jan 2017

Cited by 26 | Viewed by 8685

Abstract

This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients [...] Read more.

This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients’ biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient’s biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios. Full article

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Open AccessArticle

Enriching Mental Health Mobile Assessment and Intervention with Situation Awareness

by Ariel Soares Teles, Artur Rocha, Francisco José da Silva e Silva, João Correia Lopes, Donal O’Sullivan, Pepijn Van de Ven and Markus Endler

Sensors 2017, 17(1), 127; https://doi.org/10.3390/s17010127 - 10 Jan 2017

Cited by 18 | Viewed by 6981

Abstract

Current mobile devices allow the execution of sophisticated applications with the capacity for identifying the user situation, which can be helpful in treatments of mental disorders. In this paper, we present SituMan, a solution that provides situation awareness to MoodBuster, an [...] Read more.

Current mobile devices allow the execution of sophisticated applications with the capacity for identifying the user situation, which can be helpful in treatments of mental disorders. In this paper, we present SituMan, a solution that provides situation awareness to MoodBuster, an ecological momentary assessment and intervention mobile application used to request self-assessments from patients in depression treatments. SituMan has a fuzzy inference engine to identify patient situations using context data gathered from the sensors embedded in mobile devices. Situations are specified jointly by the patient and mental health professional, and they can represent the patient’s daily routine (e.g., “studying”, “at work”, “working out”). MoodBuster requests mental status self-assessments from patients at adequate moments using situation awareness. In addition, SituMan saves and displays patient situations in a summary, delivering them for consultation by mental health professionals. A first experimental evaluation was performed to assess the user satisfaction with the approaches to define and identify situations. This experiment showed that SituMan was well evaluated in both criteria. A second experiment was performed to assess the accuracy of the fuzzy engine to infer situations. Results from the second experiment showed that the fuzzy inference engine has a good accuracy to identify situations. Full article

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Open AccessArticle

A Non-Invasive Multichannel Hybrid Fiber-Optic Sensor System for Vital Sign Monitoring

by Marcel Fajkus, Jan Nedoma, Radek Martinek, Vladimir Vasinek, Homer Nazeran and Petr Siska

Sensors 2017, 17(1), 111; https://doi.org/10.3390/s17010111 - 8 Jan 2017

Cited by 153 | Viewed by 11111

Abstract

In this article, we briefly describe the design, construction, and functional verification of a hybrid multichannel fiber-optic sensor system for basic vital sign monitoring. This sensor uses a novel non-invasive measurement probe based on the fiber Bragg grating (FBG). The probe is composed [...] Read more.

In this article, we briefly describe the design, construction, and functional verification of a hybrid multichannel fiber-optic sensor system for basic vital sign monitoring. This sensor uses a novel non-invasive measurement probe based on the fiber Bragg grating (FBG). The probe is composed of two FBGs encapsulated inside a polydimethylsiloxane polymer (PDMS). The PDMS is non-reactive to human skin and resistant to electromagnetic waves, UV absorption, and radiation. We emphasize the construction of the probe to be specifically used for basic vital sign monitoring such as body temperature, respiratory rate and heart rate. The proposed sensor system can continuously process incoming signals from up to 128 individuals. We first present the overall design of this novel multichannel sensor and then elaborate on how it has the potential to simplify vital sign monitoring and consequently improve the comfort level of patients in long-term health care facilities, hospitals and clinics. The reference ECG signal was acquired with the use of standard gel electrodes fixed to the monitored person's chest using a real-time monitoring system for ECG signals with virtual instrumentation. The outcomes of these experiments have unambiguously proved the functionality of the sensor system and will be used to inform our future research in this fast developing and emerging field. Full article

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Open AccessArticle

Pruning-Based Sparse Recovery for Electrocardiogram Reconstruction from Compressed Measurements

by Jaeseok Lee, Kyungsoo Kim and Ji-Woong Choi

Sensors 2017, 17(1), 105; https://doi.org/10.3390/s17010105 - 7 Jan 2017

Cited by 3 | Viewed by 6220

Abstract

Due to the necessity of the low-power implementation of newly-developed electrocardiogram (ECG) sensors, exact ECG data reconstruction from the compressed measurements has received much attention in recent years. Our interest lies in improving the compression ratio (CR), as well as the ECG reconstruction [...] Read more.

Due to the necessity of the low-power implementation of newly-developed electrocardiogram (ECG) sensors, exact ECG data reconstruction from the compressed measurements has received much attention in recent years. Our interest lies in improving the compression ratio (CR), as well as the ECG reconstruction performance of the sparse signal recovery. To this end, we propose a sparse signal reconstruction method by pruning-based tree search, which attempts to choose the globally-optimal solution by minimizing the cost function. In order to achieve low complexity for the real-time implementation, we employ a novel pruning strategy to avoid exhaustive tree search. Through the restricted isometry property (RIP)-based analysis, we show that the exact recovery condition of our approach is more relaxed than any of the existing methods. Through the simulations, we demonstrate that the proposed approach outperforms the existing sparse recovery methods for ECG reconstruction. Full article

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2016

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Open AccessArticle

Wearable IMU for Shoulder Injury Prevention in Overhead Sports

by Samir A. Rawashdeh, Derek A. Rafeldt and Timothy L. Uhl

Sensors 2016, 16(11), 1847; https://doi.org/10.3390/s16111847 - 3 Nov 2016

Cited by 62 | Viewed by 14095

Abstract

Body-worn inertial sensors have enabled motion capture outside of the laboratory setting. In this work, an inertial measurement unit was attached to the upper arm to track and discriminate between shoulder motion gestures in order to help prevent shoulder over-use injuries in athletics [...] Read more.

Body-worn inertial sensors have enabled motion capture outside of the laboratory setting. In this work, an inertial measurement unit was attached to the upper arm to track and discriminate between shoulder motion gestures in order to help prevent shoulder over-use injuries in athletics through real-time preventative feedback. We present a detection and classification approach that can be used to count the number of times certain motion gestures occur. The application presented involves tracking baseball throws and volleyball serves, which are common overhead movements that can lead to shoulder and elbow overuse injuries. Eleven subjects are recruited to collect training, testing, and randomized validation data, which include throws, serves, and seven other exercises that serve as a large null class of similar movements, which is analogous to a realistic usage scenario and requires a robust estimator. Full article

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Open AccessArticle

Wheelchair Navigation System for Disabled and Elderly People

by Eun Yi Kim

Sensors 2016, 16(11), 1806; https://doi.org/10.3390/s16111806 - 28 Oct 2016

Cited by 30 | Viewed by 15544

Abstract

An intelligent wheelchair (IW) system is developed in order to support safe mobility for disabled or elderly people with various impairments. The proposed IW offers two main functions: obstacle detection and avoidance, and situation recognition. First, through a combination of a vision sensor [...] Read more.

An intelligent wheelchair (IW) system is developed in order to support safe mobility for disabled or elderly people with various impairments. The proposed IW offers two main functions: obstacle detection and avoidance, and situation recognition. First, through a combination of a vision sensor and eight ultrasonic ones, it detects diverse obstacles and produces occupancy grid maps (OGMs) that describe environmental information, including the positions and sizes of obstacles, which is then given to the learning-based algorithm. By learning the common patterns among OGMs assigned to the same directions, the IW can automatically find paths to prevent collisions with obstacles. Second, it distinguishes a situation whereby the user is standing on a sidewalk, traffic intersection, or roadway through analyzing the texture and shape of the images, which aids in preventing any accidents that would result in fatal injuries to the user, such as collisions with vehicles. From the experiments that were performed in various environments, we can prove the following: (1) the proposed system can recognize different types of outdoor places with 98.3% accuracy; and (2) it can produce paths that avoid obstacles with 92.0% accuracy. Full article

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Open AccessArticle

Skeleton-Based Abnormal Gait Detection

by Trong-Nguyen Nguyen, Huu-Hung Huynh and Jean Meunier

Sensors 2016, 16(11), 1792; https://doi.org/10.3390/s16111792 - 26 Oct 2016

Cited by 63 | Viewed by 10620

Abstract

Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an [...] Read more.

Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%. Full article

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Open AccessArticle

Assessing Walking Strategies Using Insole Pressure Sensors for Stroke Survivors

by Mario Munoz-Organero, Jack Parker, Lauren Powell and Susan Mawson

Sensors 2016, 16(10), 1631; https://doi.org/10.3390/s16101631 - 1 Oct 2016

Cited by 27 | Viewed by 9229

Abstract

Insole pressure sensors capture the different forces exercised over the different parts of the sole when performing tasks standing up such as walking. Using data analysis and machine learning techniques, common patterns and strategies from different users to achieve different tasks can be [...] Read more.

Insole pressure sensors capture the different forces exercised over the different parts of the sole when performing tasks standing up such as walking. Using data analysis and machine learning techniques, common patterns and strategies from different users to achieve different tasks can be automatically extracted. In this paper, we present the results obtained for the automatic detection of different strategies used by stroke survivors when walking as integrated into an Information Communication Technology (ICT) enhanced Personalised Self-Management Rehabilitation System (PSMrS) for stroke rehabilitation. Fourteen stroke survivors and 10 healthy controls have participated in the experiment by walking six times a distance from chair to chair of approximately 10 m long. The Rivermead Mobility Index was used to assess the functional ability of each individual in the stroke survivor group. Several walking strategies are studied based on data gathered from insole pressure sensors and patterns found in stroke survivor patients are compared with average patterns found in healthy control users. A mechanism to automatically estimate a mobility index based on the similarity of the pressure patterns to a stereotyped stride is also used. Both data gathered from stroke survivors and healthy controls are used to evaluate the proposed mechanisms. The output of trained algorithms is applied to the PSMrS system to provide feedback on gait quality enabling stroke survivors to self-manage their rehabilitation. Full article

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Open AccessReview

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

by José Jair Alves Mendes Jr., Mário Elias Marinho Vieira, Marcelo Bissi Pires and Sergio Luiz Stevan Jr.

Sensors 2016, 16(10), 1569; https://doi.org/10.3390/s16101569 - 23 Sep 2016

Cited by 91 | Viewed by 24006

Abstract

The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical [...] Read more.

The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others. Full article

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Open AccessArticle

Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

by Meina Li, Keun-Chang Kwak and Youn Tae Kim

Sensors 2016, 16(10), 1566; https://doi.org/10.3390/s16101566 - 22 Sep 2016

Cited by 9 | Viewed by 5704

Abstract

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop [...] Read more.

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model. Full article

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Open AccessArticle

Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction

by Md Golam Rabiul Alam, Sarder Fakhrul Abedin, Moshaddique Al Ameen and Choong Seon Hong

Sensors 2016, 16(9), 1431; https://doi.org/10.3390/s16091431 - 6 Sep 2016

Cited by 20 | Viewed by 7547

Abstract

Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients’ psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning [...] Read more.

Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients’ psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller’s mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study. Full article

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Open AccessReview

Techniques for Interface Stress Measurements within Prosthetic Sockets of Transtibial Amputees: A Review of the Past 50 Years of Research

by Ebrahim A. Al-Fakih, Noor Azuan Abu Osman and Faisal Rafiq Mahmad Adikan

Sensors 2016, 16(7), 1119; https://doi.org/10.3390/s16071119 - 20 Jul 2016

Cited by 66 | Viewed by 17153

Abstract

The distribution of interface stresses between the residual limb and prosthetic socket of a transtibial amputee has been considered as a direct indicator of the socket quality fit and comfort. Therefore, researchers have been very interested in quantifying these interface stresses in order [...] Read more.

The distribution of interface stresses between the residual limb and prosthetic socket of a transtibial amputee has been considered as a direct indicator of the socket quality fit and comfort. Therefore, researchers have been very interested in quantifying these interface stresses in order to evaluate the extent of any potential damage caused by the socket to the residual limb tissues. During the past 50 years a variety of measurement techniques have been employed in an effort to identify sites of excessive stresses which may lead to skin breakdown, compare stress distributions in various socket designs, and evaluate interface cushioning and suspension systems, among others. The outcomes of such measurement techniques have contributed to improving the design and fitting of transtibial sockets. This article aims to review the operating principles, advantages, and disadvantages of conventional and emerging techniques used for interface stress measurements inside transtibial sockets. It also reviews and discusses the evolution of different socket concepts and interface stress investigations conducted in the past five decades, providing valuable insights into the latest trends in socket designs and the crucial considerations for effective stress measurement tools that lead to a functional prosthetic socket. Full article

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Open AccessArticle

Stair-Walking Performance in Adolescents with Intellectual Disabilities

by Wann-Yun Shieh, Yan-Ying Ju, Yu-Chun Yu, Che-Kuan Lin, Yen-Tzu Lin and Hsin-Yi Kathy Cheng

Sensors 2016, 16(7), 1066; https://doi.org/10.3390/s16071066 - 11 Jul 2016

Cited by 9 | Viewed by 6264

Abstract

Most individuals with intellectual disabilities (ID) demonstrate problems in learning and movement coordination. Consequently, they usually have difficulties in activities such as standing, walking, and stair climbing. To monitor the physical impairments of these children, regular gross motor evaluation is crucial. Straight-line level [...] Read more.

Most individuals with intellectual disabilities (ID) demonstrate problems in learning and movement coordination. Consequently, they usually have difficulties in activities such as standing, walking, and stair climbing. To monitor the physical impairments of these children, regular gross motor evaluation is crucial. Straight-line level walking is the most frequently used test of their mobility. However, numerous studies have found that unless the children have multiple disabilities, no significant differences can be found between the children with ID and typically-developed children in this test. Stair climbing presents more challenges than level walking because it is associated with numerous physical factors, including lower extremity strength, cardiopulmonary endurance, vision, balance, and fear of falling. Limited ability in those factors is one of the most vital markers for children with ID. In this paper, we propose a sensor-based approach for measuring stair-walking performance, both upstairs and downstairs, for adolescents with ID. Particularly, we address the problem of sensor calibration to ensure measurement accuracy. In total, 62 participants aged 15 to 21 years, namely 32 typically-developed (TD) adolescents, 20 adolescents with ID, and 10 adolescents with multiple disabilities (MD), participated. The experimental results showed that stair-walking is more sensitive than straight-line level walking in capturing gait characteristics for adolescents with ID. Full article

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Open AccessArticle

On Curating Multimodal Sensory Data for Health and Wellness Platforms

by Muhammad Bilal Amin, Oresti Banos, Wajahat Ali Khan, Hafiz Syed Muhammad Bilal, Jinhyuk Gong, Dinh-Mao Bui, Soung Ho Cho, Shujaat Hussain, Taqdir Ali, Usman Akhtar, Tae Choong Chung and Sungyoung Lee

Sensors 2016, 16(7), 980; https://doi.org/10.3390/s16070980 - 27 Jun 2016

Cited by 37 | Viewed by 9384

Abstract

In recent years, the focus of healthcare and wellness technologies has shown a significant shift towards personal vital signs devices. The technology has evolved from smartphone-based wellness applications to fitness bands and smartwatches. The novelty of these devices is the accumulation of activity [...] Read more.

In recent years, the focus of healthcare and wellness technologies has shown a significant shift towards personal vital signs devices. The technology has evolved from smartphone-based wellness applications to fitness bands and smartwatches. The novelty of these devices is the accumulation of activity data as their users go about their daily life routine. However, these implementations are device specific and lack the ability to incorporate multimodal data sources. Data accumulated in their usage does not offer rich contextual information that is adequate for providing a holistic view of a user’s lifelog. As a result, making decisions and generating recommendations based on this data are single dimensional. In this paper, we present our Data Curation Framework (DCF) which is device independent and accumulates a user’s sensory data from multimodal data sources in real time. DCF curates the context of this accumulated data over the user’s lifelog. DCF provides rule-based anomaly detection over this context-rich lifelog in real time. To provide computation and persistence over the large volume of sensory data, DCF utilizes the distributed and ubiquitous environment of the cloud platform. DCF has been evaluated for its performance, correctness, ability to detect complex anomalies, and management support for a large volume of sensory data. Full article

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Open AccessArticle

Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson’s Disease

by Neltje E. Piro, Lennart K. Piro, Jan Kassubek and Ronald A. Blechschmidt-Trapp

Sensors 2016, 16(6), 930; https://doi.org/10.3390/s16060930 - 21 Jun 2016

Cited by 24 | Viewed by 9988

Abstract

Remote monitoring of Parkinson’s Disease (PD) patients with inertia sensors is a relevant method for a better assessment of symptoms. We present a new approach for symptom quantification based on motion data: the automatic Unified Parkinson Disease Rating Scale (UPDRS) classification in combination [...] Read more.

Remote monitoring of Parkinson’s Disease (PD) patients with inertia sensors is a relevant method for a better assessment of symptoms. We present a new approach for symptom quantification based on motion data: the automatic Unified Parkinson Disease Rating Scale (UPDRS) classification in combination with an animated 3D avatar giving the neurologist the impression of having the patient live in front of him. In this study we compared the UPDRS ratings of the pronation-supination task derived from: (a) an examination based on video recordings as a clinical reference; (b) an automatically classified UPDRS; and (c) a UPDRS rating from the assessment of the animated 3D avatar. Data were recorded using Magnetic, Angular Rate, Gravity (MARG) sensors with 15 subjects performing a pronation-supination movement of the hand. After preprocessing, the data were classified with a J48 classifier and animated as a 3D avatar. Video recording of the movements, as well as the 3D avatar, were examined by movement disorder specialists and rated by UPDRS. The mean agreement between the ratings based on video and (b) the automatically classified UPDRS is 0.48 and with (c) the 3D avatar it is 0.47. The 3D avatar is similarly suitable for assessing the UPDRS as video recordings for the examined task and will be further developed by the research team. Full article

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Open AccessReview

A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments

by Mohammad Ghamari, Balazs Janko, R. Simon Sherratt, William Harwin, Robert Piechockic and Cinna Soltanpur

Sensors 2016, 16(6), 831; https://doi.org/10.3390/s16060831 - 7 Jun 2016

Cited by 250 | Viewed by 32527

Abstract

Current progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological [...] Read more.

Current progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological parameters. Collected data are relayed using existing wireless communication protocols to a base station for additional processing. This article provides researchers with information to compare the existing low-power communication technologies that can potentially support the rapid development and deployment of WBAN systems, and mainly focuses on remote monitoring of elderly or chronically ill patients in residential environments. Full article

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Open AccessArticle

A Wireless Pressure Sensor Integrated with a Biodegradable Polymer Stent for Biomedical Applications

by Jongsung Park, Ji-Kwan Kim, Swati J. Patil, Jun-Kyu Park, SuA Park and Dong-Weon Lee

Sensors 2016, 16(6), 809; https://doi.org/10.3390/s16060809 - 2 Jun 2016

Cited by 80 | Viewed by 13335

Abstract

This paper describes the fabrication and characterization of a wireless pressure sensor for smart stent applications. The micromachined pressure sensor has an area of 3.13 × 3.16 mm² and is fabricated with a photosensitive SU-8 polymer. The wireless pressure sensor comprises a [...] Read more.

This paper describes the fabrication and characterization of a wireless pressure sensor for smart stent applications. The micromachined pressure sensor has an area of 3.13 × 3.16 mm² and is fabricated with a photosensitive SU-8 polymer. The wireless pressure sensor comprises a resonant circuit and can be used without the use of an internal power source. The capacitance variations caused by changes in the intravascular pressure shift the resonance frequency of the sensor. This change can be detected using an external antenna, thus enabling the measurement of the pressure changes inside a tube with a simple external circuit. The wireless pressure sensor is capable of measuring pressure from 0 mmHg to 230 mmHg, with a sensitivity of 0.043 MHz/mmHg. The biocompatibility of the pressure sensor was evaluated using cardiac cells isolated from neonatal rat ventricular myocytes. After inserting a metal stent integrated with the pressure sensor into a cardiovascular vessel of an animal, medical systems such as X-ray were employed to consistently monitor the condition of the blood vessel. No abnormality was found in the animal blood vessel for approximately one month. Furthermore, a biodegradable polymer (polycaprolactone) stent was fabricated with a 3D printer. The polymer stent exhibits better sensitivity degradation of the pressure sensor compared to the metal stent. Full article

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Open AccessArticle

A Dual-Field Sensing Scheme for a Guidance System for the Blind

by Qing Lin and Youngjoon Han

Sensors 2016, 16(5), 667; https://doi.org/10.3390/s16050667 - 11 May 2016

Cited by 6 | Viewed by 6703

Abstract

An electronic guidance system is very helpful in improving blind people’s perceptions in a local environment. In our previous work “Lin, Q.; Han, Y. A Context-Aware-Based Audio Guidance System for Blind People Using a Multimodal Profile Model. Sensors 2014, 14, 18670–18700”, a context-aware [...] Read more.

An electronic guidance system is very helpful in improving blind people’s perceptions in a local environment. In our previous work “Lin, Q.; Han, Y. A Context-Aware-Based Audio Guidance System for Blind People Using a Multimodal Profile Model. Sensors 2014, 14, 18670–18700”, a context-aware guidance system using a combination of a laser scanner and a camera was proposed. By using a near-field graphical model, the proposed system could interpret a near-field scene in very high resolution. In this paper, our work is extended by adding a far-field graphical model. The integration of the near-field and the far-field models constitutes a dual-field sensing scheme. In the near-field range, reliable inference of the ground and object status is obtained by fusing range data and image data using the near-field graphical model. In the far-field range, which only the camera can cover, the far-field graphical model is proposed to interpret far-field image data based on appearance and spatial prototypes built using the near-field interpreted data. The dual-field sensing scheme provides a solution for the guidance systems to optimise their scene interpretation capability using simple sensor configurations. Experiments under various local conditions were conducted to show the efficiency of the proposed scheme in improving blind people’s perceptions in urban environments. Full article

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Open AccessArticle

Physiological Signal Monitoring Bed for Infants Based on Load-Cell Sensors

by Won Kyu Lee, Heenam Yoon, Chungmin Han, Kwang Min Joo and Kwang Suk Park

Sensors 2016, 16(3), 409; https://doi.org/10.3390/s16030409 - 19 Mar 2016

Cited by 48 | Viewed by 11212

Abstract

Ballistocardiographs (BCGs), which record the mechanical activity of the heart, have been a subject of interest for several years because of their advantages in providing unobtrusive physiological measurements. BCGs could also be useful for monitoring the biological signals of infants without the need [...] Read more.

Ballistocardiographs (BCGs), which record the mechanical activity of the heart, have been a subject of interest for several years because of their advantages in providing unobtrusive physiological measurements. BCGs could also be useful for monitoring the biological signals of infants without the need for physical confinement. In this study, we describe a physiological signal monitoring bed based on load cells and assess an algorithm to extract the heart rate and breathing rate from the measured load-cell signals. Four infants participated in a total of 13 experiments. As a reference signal, electrocardiogram and respiration signals were simultaneously measured using a commercial device. The proposed automatic algorithm then selected the optimal sensor from which to estimate the heartbeat and respiration information. The results from the load-cell sensor signals were compared with those of the reference signals, and the heartbeat and respiration information were found to have average performance errors of 2.55% and 2.66%, respectively. The experimental results verify the positive feasibility of BCG-based measurements in infants. Full article

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2015

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Open AccessArticle

Tilted Orientation of Photochromic Dyes with Guest-Host Effect of Liquid Crystalline Polymer Matrix for Electrical UV Sensing

by Amid Ranjkesh, Min-Kyu Park, Do Hyuk Park, Ji-Sub Park, Jun-Chan Choi, Sung-Hoon Kim and Hak-Rin Kim

Sensors 2016, 16(1), 38; https://doi.org/10.3390/s16010038 - 29 Dec 2015

Cited by 7 | Viewed by 7537

Abstract

We propose a highly oriented photochromic dye film for an ultraviolet (UV)-sensing layer, where spirooxazine (SO) derivatives are aligned with the liquid crystalline UV-curable reactive mesogens (RM) using a guest-host effect. For effective electrical UV sensing with a simple metal-insulator-metal structure, our results [...] Read more.

We propose a highly oriented photochromic dye film for an ultraviolet (UV)-sensing layer, where spirooxazine (SO) derivatives are aligned with the liquid crystalline UV-curable reactive mesogens (RM) using a guest-host effect. For effective electrical UV sensing with a simple metal-insulator-metal structure, our results show that the UV-induced switchable dipole moment amount of the SO derivatives is high; however, their tilting orientation should be controlled. Compared to the dielectric layer with the nearly planar SO dye orientation, the photochromic dielectric layer with the moderately tilted dye orientation shows more than seven times higher the UV-induced capacitance variation. Full article

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Open AccessArticle

One Small Step for a Man: Estimation of Gender, Age and Height from Recordings of One Step by a Single Inertial Sensor

by Qaiser Riaz, Anna Vögele, Björn Krüger and Andreas Weber

Sensors 2015, 15(12), 31999-32019; https://doi.org/10.3390/s151229907 - 19 Dec 2015

Cited by 58 | Viewed by 8454

Abstract

A number of previous works have shown that information about a subject is encoded in sparse kinematic information, such as the one revealed by so-called point light walkers. With the work at hand, we extend these results to classifications of soft biometrics from [...] Read more.

A number of previous works have shown that information about a subject is encoded in sparse kinematic information, such as the one revealed by so-called point light walkers. With the work at hand, we extend these results to classifications of soft biometrics from inertial sensor recordings at a single body location from a single step. We recorded accelerations and angular velocities of 26 subjects using integrated measurement units (IMUs) attached at four locations (chest, lower back, right wrist and left ankle) when performing standardized gait tasks. The collected data were segmented into individual walking steps. We trained random forest classifiers in order to estimate soft biometrics (gender, age and height). We applied two different validation methods to the process, 10-fold cross-validation and subject-wise cross-validation. For all three classification tasks, we achieve high accuracy values for all four sensor locations. From these results, we can conclude that the data of a single walking step (6D: accelerations and angular velocities) allow for a robust estimation of the gender, height and age of a person. Full article

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Open AccessArticle

Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms

by Shengyun Liang, Yunkun Ning, Huiqi Li, Lei Wang, Zhanyong Mei, Yingnan Ma and Guoru Zhao

Sensors 2015, 15(11), 29393-29407; https://doi.org/10.3390/s151129393 - 20 Nov 2015

Cited by 27 | Viewed by 8382

Abstract

The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent [...] Read more.

The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF) data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers) participated in functional movement tests, including walking and sit-to-stand (STS). A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN), pseudo nearest neighbor (PNN), local mean pseudo nearest neighbor (LMPNN) classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population. Full article

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Open AccessArticle

Identification of Foot Pathologies Based on Plantar Pressure Asymmetry

by Linah Wafai, Aladin Zayegh, John Woulfe, Syed Mahfuzul Aziz and Rezaul Begg

Sensors 2015, 15(8), 20392-20408; https://doi.org/10.3390/s150820392 - 18 Aug 2015

Cited by 106 | Viewed by 22816

Abstract

Foot pathologies can negatively influence foot function, consequently impairing gait during daily activity, and severely impacting an individual’s quality of life. These pathologies are often painful and correspond with high or abnormal plantar pressure, which can result in asymmetry in the pressure distribution [...] Read more.

Foot pathologies can negatively influence foot function, consequently impairing gait during daily activity, and severely impacting an individual’s quality of life. These pathologies are often painful and correspond with high or abnormal plantar pressure, which can result in asymmetry in the pressure distribution between the two feet. There is currently no general consensus on the presence of asymmetry in able-bodied gait, and plantar pressure analysis during gait is in dire need of a standardized method to quantify asymmetry. This paper investigates the use of plantar pressure asymmetry for pathological gait diagnosis. The results of this study involving plantar pressure analysis in fifty one participants (31 healthy and 20 with foot pathologies) support the presence of plantar pressure asymmetry in normal gait. A higher level of asymmetry was detected at the majority of the regions in the feet of the pathological population, including statistically significant differences in the plantar pressure asymmetry in two regions of the foot, metatarsophalangeal joint 3 (MPJ3) and the lateral heel. Quantification of plantar pressure asymmetry may prove to be useful for the identification and diagnosis of various foot pathologies. Full article

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Open AccessArticle

Improved Measurement of Blood Pressure by Extraction of Characteristic Features from the Cuff Oscillometric Waveform

by Pooi Khoon Lim, Siew-Cheok Ng, Wissam A. Jassim, Stephen J. Redmond, Mohammad Zilany, Alberto Avolio, Einly Lim, Maw Pin Tan and Nigel H. Lovell

Sensors 2015, 15(6), 14142-14161; https://doi.org/10.3390/s150614142 - 16 Jun 2015

Cited by 20 | Viewed by 9852

Abstract

We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 [...] Read more.

We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 ± 5 years. The multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the relationship between the SBP and the DBP ratio with ten features extracted from the oscillometric waveform envelope (OWE). An automatic algorithm based on relative changes in the cuff pressure and neighbouring oscillometric pulses was proposed to remove outlier points caused by movement artifacts. Substantial reduction in the mean and standard deviation of the blood pressure estimation errors were obtained upon artifact removal. Using the sequential forward floating selection (SFFS) approach, we were able to achieve a significant reduction in the mean and standard deviation of differences between the estimated SBP values and the reference scoring (MLR: mean ± SD = −0.3 ± 5.8 mmHg; SVR and −0.6 ± 5.4 mmHg) with only two features, i.e., Ratio₂ and Area₃, as compared to the conventional maximum amplitude algorithm (MAA) method (mean ± SD = −1.6 ± 8.6 mmHg). Comparing the performance of both MLR and SVR models, our results showed that the MLR model was able to achieve comparable performance to that of the SVR model despite its simplicity. Full article

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Open AccessArticle

A Wavelet-Based Approach to Fall Detection

by Luca Palmerini, Fabio Bagalà, Andrea Zanetti, Jochen Klenk, Clemens Becker and Angelo Cappello

Sensors 2015, 15(5), 11575-11586; https://doi.org/10.3390/s150511575 - 20 May 2015

Cited by 41 | Viewed by 8455

Abstract

Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based [...] Read more.

Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based approach to fall detection, focusing on the impact phase and using a dataset of real-world falls. Since recorded falls result in a non-stationary signal, a wavelet transform was chosen to examine fall patterns. The idea is to consider the average fall pattern as the “prototype fall”.In order to detect falls, every acceleration signal can be compared to this prototype through wavelet analysis. The similarity of the recorded signal with the prototype fall is a feature that can be used in order to determine the difference between falls and daily activities. The discriminative ability of this feature is evaluated on real-world data. It outperforms other features that are commonly used in fall detection studies, with an Area Under the Curve of 0.918. This result suggests that the proposed wavelet-based feature is promising and future studies could use this feature (in combination with others considering different fall phases) in order to improve the performance of fall detection algorithms. Full article

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Open AccessReview

The Elderly’s Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development

by Qin Ni, Ana Belén García Hernando and Iván Pau De la Cruz

Sensors 2015, 15(5), 11312-11362; https://doi.org/10.3390/s150511312 - 14 May 2015

Cited by 211 | Viewed by 18600

Abstract

Human activity detection within smart homes is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of “activity” as the building block with which to construct applications such [...] Read more.

Human activity detection within smart homes is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of “activity” as the building block with which to construct applications such as healthcare monitoring or ambient assisted living. The process of identifying a specific activity encompasses the selection of the appropriate set of sensors, the correct preprocessing of their provided raw data and the learning/reasoning using this information. If the selection of the sensors and the data processing methods are wrongly performed, the whole activity detection process may fail, leading to the consequent failure of the whole application. Related to this, the main contributions of this review are the following: first, we propose a classification of the main activities considered in smart home scenarios which are targeted to older people’s independent living, as well as their characterization and formalized context representation; second, we perform a classification of sensors and data processing methods that are suitable for the detection of the aforementioned activities. Our aim is to help researchers and developers in these lower-level technical aspects that are nevertheless fundamental for the success of the complete application. Full article

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Open AccessArticle

Heart Rate Variability Monitoring during Sleep Based on Capacitively Coupled Textile Electrodes on a Bed

by Hong Ji Lee, Su Hwan Hwang, Hee Nam Yoon, Won Kyu Lee and Kwang Suk Park

Sensors 2015, 15(5), 11295-11311; https://doi.org/10.3390/s150511295 - 14 May 2015

Cited by 55 | Viewed by 9866

Abstract

In this study, we developed and tested a capacitively coupled electrocardiogram (ECG) measurement system using conductive textiles on a bed, for long-term healthcare monitoring. The system, which was designed to measure ECG in a bed with no constraints of sleep position and posture, [...] Read more.

In this study, we developed and tested a capacitively coupled electrocardiogram (ECG) measurement system using conductive textiles on a bed, for long-term healthcare monitoring. The system, which was designed to measure ECG in a bed with no constraints of sleep position and posture, included a foam layer to increase the contact region with the curvature of the body and a cover to ensure durability and easy installation. Nine healthy subjects participated in the experiment during polysomnography (PSG), and the heart rate (HR) coverage and heart rate variability (HRV) parameters were analyzed to evaluate the system. The experimental results showed that the mean of R-peak coverage was 98.0% (95.5%–99.7%), and the normalized errors of HRV time and spectral measures between the Ag/AgCl system and our system ranged from 0.15% to 4.20%. The root mean square errors for inter-beat (RR) intervals and HR were 1.36 ms and 0.09 bpm, respectively. We also showed the potential of our developed system for rapid eye movement (REM) sleep and wake detection as well as for recording of abnormal states. Full article

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Open AccessArticle

Tracking Systems for Virtual Rehabilitation: Objective Performance vs. Subjective Experience. A Practical Scenario

by Roberto Lloréns, Enrique Noé, Valery Naranjo, Adrián Borrego, Jorge Latorre and Mariano Alcañiz

Sensors 2015, 15(3), 6586-6606; https://doi.org/10.3390/s150306586 - 19 Mar 2015

Cited by 22 | Viewed by 8817

Abstract

Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements [...] Read more.

Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking) in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 ± 0.417 cm) while the electromagnetic device provided the most inaccurate results (11.027 ± 2.364 cm). However, this tracking solution provided the best jitter values (0.324 ± 0.093 cm), in contrast to the skeleton tracking, which had the worst results (1.522 ± 0.858 cm). Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order). Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system. Full article

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Open AccessArticle

New Lower-Limb Gait Asymmetry Indices Based on a Depth Camera

by Edouard Auvinet, Franck Multon and Jean Meunier

Sensors 2015, 15(3), 4605-4623; https://doi.org/10.3390/s150304605 - 24 Feb 2015

Cited by 34 | Viewed by 9787

Abstract

Background: Various asymmetry indices have been proposed to compare the spatiotemporal, kinematic and kinetic parameters of lower limbs during the gait cycle. However, these indices rely on gait measurement systems that are costly and generally require manual examination, calibration procedures and the precise [...] Read more.

Background: Various asymmetry indices have been proposed to compare the spatiotemporal, kinematic and kinetic parameters of lower limbs during the gait cycle. However, these indices rely on gait measurement systems that are costly and generally require manual examination, calibration procedures and the precise placement of sensors/markers on the body of the patient. Methods: To overcome these issues, this paper proposes a new asymmetry index, which uses an inexpensive, easy-to-use and markerless depth camera (Microsoft Kinect™) output. This asymmetry index directly uses depth images provided by the Kinect™ without requiring joint localization. It is based on the longitudinal spatial difference between lower-limb movements during the gait cycle. To evaluate the relevance of this index, fifteen healthy subjects were tested on a treadmill walking normally and then via an artificially-induced gait asymmetry with a thick sole placed under one shoe. The gait movement was simultaneously recorded using a Kinect™ placed in front of the subject and a motion capture system. Results: The proposed longitudinal index distinguished asymmetrical gait (p < 0.001), while other symmetry indices based on spatiotemporal gait parameters failed using such Kinect™ skeleton measurements. Moreover, the correlation coefficient between this index measured by Kinect™ and the ground truth of this index measured by motion capture is 0.968. Conclusion: This gait asymmetry index measured with a Kinect™ is low cost, easy to use and is a promising development for clinical gait analysis. Full article

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Open AccessArticle

False Alarm Reduction in BSN-Based Cardiac Monitoring Using Signal Quality and Activity Type Information

by Tanatorn Tanantong, Ekawit Nantajeewarawat and Surapa Thiemjarus

Sensors 2015, 15(2), 3952-3974; https://doi.org/10.3390/s150203952 - 9 Feb 2015

Cited by 15 | Viewed by 9715

Abstract

False alarms in cardiac monitoring affect the quality of medical care, impacting on both patients and healthcare providers. In continuous cardiac monitoring using wireless Body Sensor Networks (BSNs), the quality of ECG signals can be deteriorated owing to several factors, e.g., noises, low [...] Read more.

False alarms in cardiac monitoring affect the quality of medical care, impacting on both patients and healthcare providers. In continuous cardiac monitoring using wireless Body Sensor Networks (BSNs), the quality of ECG signals can be deteriorated owing to several factors, e.g., noises, low battery power, and network transmission problems, often resulting in high false alarm rates. In addition, body movements occurring from activities of daily living (ADLs) can also create false alarms. This paper presents a two-phase framework for false arrhythmia alarm reduction in continuous cardiac monitoring, using signals from an ECG sensor and a 3D accelerometer. In the first phase, classification models constructed using machine learning algorithms are used for labeling input signals. ECG signals are labeled with heartbeat types and signal quality levels, while 3D acceleration signals are labeled with ADL types. In the second phase, a rule-based expert system is used for combining classification results in order to determine whether arrhythmia alarms should be accepted or suppressed. The proposed framework was validated on datasets acquired using BSNs and the MIT-BIH arrhythmia database. For the BSN dataset, acceleration and ECG signals were collected from 10 young and 10 elderly subjects while they were performing ADLs. The framework reduced the false alarm rate from 9.58% to 1.43% in our experimental study, showing that it can potentially assist physicians in diagnosing a vast amount of data acquired from wireless sensors and enhance the performance of continuous cardiac monitoring. Full article

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Open AccessArticle

Embroidered Electrode with Silver/Titanium Coating for Long-Term ECG Monitoring

by Markus Weder, Dirk Hegemann, Martin Amberg, Markus Hess, Luciano F. Boesel, Roger Abächerli, Veronika R. Meyer and René M. Rossi

Sensors 2015, 15(1), 1750-1759; https://doi.org/10.3390/s150101750 - 15 Jan 2015

Cited by 105 | Viewed by 14012

Abstract

For the long-time monitoring of electrocardiograms, electrodes must be skin-friendly and non-irritating, but in addition they must deliver leads without artifacts even if the skin is dry and the body is moving. Today’s adhesive conducting gel electrodes are not suitable for such applications. [...] Read more.

For the long-time monitoring of electrocardiograms, electrodes must be skin-friendly and non-irritating, but in addition they must deliver leads without artifacts even if the skin is dry and the body is moving. Today’s adhesive conducting gel electrodes are not suitable for such applications. We have developed an embroidered textile electrode from polyethylene terephthalate yarn which is plasma-coated with silver for electrical conductivity and with an ultra-thin titanium layer on top for passivation. Two of these electrodes are embedded into a breast belt. They are moisturized with a very low amount of water vapor from an integrated reservoir. The combination of silver, titanium and water vapor results in an excellent electrode chemistry. With this belt the long-time monitoring of electrocardiography (ECG) is possible at rest as well as when the patient is moving. Full article

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Open AccessArticle

Kinect as a Tool for Gait Analysis: Validation of a Real-Time Joint Extraction Algorithm Working in Side View

by Enea Cippitelli, Samuele Gasparrini, Susanna Spinsante and Ennio Gambi

Sensors 2015, 15(1), 1417-1434; https://doi.org/10.3390/s150101417 - 14 Jan 2015

Cited by 51 | Viewed by 9982

Abstract

The Microsoft Kinect sensor has gained attention as a tool for gait analysis for several years. Despite the many advantages the sensor provides, however, the lack of a native capability to extract joints from the side view of a human body still limits [...] Read more.

The Microsoft Kinect sensor has gained attention as a tool for gait analysis for several years. Despite the many advantages the sensor provides, however, the lack of a native capability to extract joints from the side view of a human body still limits the adoption of the device to a number of relevant applications. This paper presents an algorithm to locate and estimate the trajectories of up to six joints extracted from the side depth view of a human body captured by the Kinect device. The algorithm is then applied to extract data that can be exploited to provide an objective score for the “Get Up and Go Test”, which is typically adopted for gait analysis in rehabilitation fields. Starting from the depth-data stream provided by the Microsoft Kinect sensor, the proposed algorithm relies on anthropometric models only, to locate and identify the positions of the joints. Differently from machine learning approaches, this solution avoids complex computations, which usually require significant resources. The reliability of the information about the joint position output by the algorithm is evaluated by comparison to a marker-based system. Tests show that the trajectories extracted by the proposed algorithm adhere to the reference curves better than the ones obtained from the skeleton generated by the native applications provided within the Microsoft Kinect (Microsoft Corporation, Redmond,WA, USA, 2013) and OpenNI (OpenNI organization, Tel Aviv, Israel, 2013) Software Development Kits. Full article

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2014

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Open AccessArticle

Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields

by Hee-Deok Yang

Sensors 2015, 15(1), 135-147; https://doi.org/10.3390/s150100135 - 24 Dec 2014

Cited by 86 | Viewed by 11478

Abstract

Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D) space. In this research, we use 3D depth information from hand motions, generated [...] Read more.

Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D) space. In this research, we use 3D depth information from hand motions, generated from Microsoft’s Kinect sensor and apply a hierarchical conditional random field (CRF) that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%. Full article

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Open AccessArticle

Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System

by Farhad Abtahi, Jonatan Snäll, Benjamin Aslamy, Shirin Abtahi, Fernando Seoane and Kaj Lindecrantz

Sensors 2015, 15(1), 93-109; https://doi.org/10.3390/s150100093 - 23 Dec 2014

Cited by 21 | Viewed by 14347

Abstract

Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping [...] Read more.

Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org. Full article

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Open AccessArticle

Assessment of a Newly Developed, Active Pneumatic-Driven, Sensorimotor Test and Training Device

by Wolfram Haslinger, Lisa Müller, Esmeralda Mildner, Stefan Löfler, Helmut Kern and Christian Raschner

Sensors 2014, 14(12), 24174-24187; https://doi.org/10.3390/s141224174 - 15 Dec 2014

Cited by 3 | Viewed by 7127

Abstract

The sensorimotor system (SMS) plays an important role in sports and in every day movement. Several tools for assessment and training have been designed. Many of them are directed to specific populations, and have major shortcomings due to the training effect or safety. [...] Read more.

The sensorimotor system (SMS) plays an important role in sports and in every day movement. Several tools for assessment and training have been designed. Many of them are directed to specific populations, and have major shortcomings due to the training effect or safety. The aim of the present study was to design and assess a dynamic sensorimotor test and training device that can be adjusted for all levels of performance. The novel pneumatic-driven mechatronic device can guide the trainee, allow independent movements or disrupt the individual with unpredicted perturbations while standing on a platform. The test-reliability was evaluated using intraclass correlation coefficient (ICC). Subjects were required to balance their center of pressure (COP) in a target circle (TITC). The time in TITC and the COP error (COPe) were recorded for analysis. The results of 22 males and 14 females (23.7 ± 2.6 years) showed good to excellent test–retest reliability. The newly designed Active Balance System (ABS) was then compared with the Biodex Balance System SD® (BBS). The results of 15 females, 14 males (23.4 ± 1.6 years) showed modest correlation in static and acceptable correlation in dynamic conditions, suggesting that ABS could be a reliable and comparable tool for dynamic balance assessments. Full article

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Open AccessArticle

Piezoelectric Bimorphs’ Characteristics as In-Socket Sensors for Transfemoral Amputees

by Amr M. El-Sayed, Nur Azah Hamzaid and Noor Azuan Abu Osman

Sensors 2014, 14(12), 23724-23741; https://doi.org/10.3390/s141223724 - 10 Dec 2014

Cited by 13 | Viewed by 8990

Abstract

Alternative sensory systems for the development of prosthetic knees are being increasingly highlighted nowadays, due to the rapid advancements in the field of lower limb prosthetics. This study presents the use of piezoelectric bimorphs as in-socket sensors for transfemoral amputees. An Instron machine [...] Read more.

Alternative sensory systems for the development of prosthetic knees are being increasingly highlighted nowadays, due to the rapid advancements in the field of lower limb prosthetics. This study presents the use of piezoelectric bimorphs as in-socket sensors for transfemoral amputees. An Instron machine was used in the calibration procedure and the corresponding output data were further analyzed to determine the static and dynamic characteristics of the piezoelectric bimorph. The piezoelectric bimorph showed appropriate static operating range, repeatability, hysteresis, and frequency response for application in lower prosthesis, with a force range of 0–100 N. To further validate this finding, an experiment was conducted with a single transfemoral amputee subject to measure the stump/socket pressure using the piezoelectric bimorph embedded inside the socket. The results showed that a maximum interface pressure of about 27 kPa occurred at the anterior proximal site compared to the anterior distal and posterior sites, consistent with values published in other studies. This paper highlighted the capacity of piezoelectric bimorphs to perform as in-socket sensors for transfemoral amputees. However, further experiments are recommended to be conducted with different amputees with different socket types. Full article

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Open AccessArticle

Drift Removal for Improving the Accuracy of Gait Parameters Using Wearable Sensor Systems

by Ryo Takeda, Giulia Lisco, Tadashi Fujisawa, Laura Gastaldi, Harukazu Tohyama and Shigeru Tadano

Sensors 2014, 14(12), 23230-23247; https://doi.org/10.3390/s141223230 - 5 Dec 2014

Cited by 72 | Viewed by 11224

Abstract

Accumulated signal noise will cause the integrated values to drift from the true value when measuring orientation angles of wearable sensors. This work proposes a novel method to reduce the effect of this drift to accurately measure human gait using wearable sensors. Firstly, [...] Read more.

Accumulated signal noise will cause the integrated values to drift from the true value when measuring orientation angles of wearable sensors. This work proposes a novel method to reduce the effect of this drift to accurately measure human gait using wearable sensors. Firstly, an infinite impulse response (IIR) digital 4th order Butterworth filter was implemented to remove the noise from the raw gyro sensor data. Secondly, the mode value of the static state gyro sensor data was subtracted from the measured data to remove offset values. Thirdly, a robust double derivative and integration method was introduced to remove any remaining drift error from the data. Lastly, sensor attachment errors were minimized by establishing the gravitational acceleration vector from the acceleration data at standing upright and sitting posture. These improvements proposed allowed for removing the drift effect, and showed an average of 2.1°, 33.3°, 15.6° difference for the hip knee and ankle joint flexion/extension angle, when compared to without implementation. Kinematic and spatio-temporal gait parameters were also calculated from the heel-contact and toe-off timing of the foot. The data provided in this work showed potential of using wearable sensors in clinical evaluation of patients with gait-related diseases. Full article

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Open AccessArticle

Long-Term Activity Recognition from Wristwatch Accelerometer Data

by Enrique Garcia-Ceja, Ramon F. Brena, Jose C. Carrasco-Jimenez and Leonardo Garrido

Sensors 2014, 14(12), 22500-22524; https://doi.org/10.3390/s141222500 - 27 Nov 2014

Cited by 64 | Viewed by 11066

Abstract

With the development of wearable devices that have several embedded sensors, it is possible to collect data that can be analyzed in order to understand the user’s needs and provide personalized services. Examples of these types of devices are smartphones, fitness-bracelets, smartwatches, just [...] Read more.

With the development of wearable devices that have several embedded sensors, it is possible to collect data that can be analyzed in order to understand the user’s needs and provide personalized services. Examples of these types of devices are smartphones, fitness-bracelets, smartwatches, just to mention a few. In the last years, several works have used these devices to recognize simple activities like running, walking, sleeping, and other physical activities. There has also been research on recognizing complex activities like cooking, sporting, and taking medication, but these generally require the installation of external sensors that may become obtrusive to the user. In this work we used acceleration data from a wristwatch in order to identify long-term activities. We compare the use of Hidden Markov Models and Conditional Random Fields for the segmentation task. We also added prior knowledge into the models regarding the duration of the activities by coding them as constraints and sequence patterns were added in the form of feature functions. We also performed subclassing in order to deal with the problem of intra-class fragmentation, which arises when the same label is applied to activities that are conceptually the same but very different from the acceleration point of view. Full article

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Open AccessArticle

Design of a Novel Flexible Capacitive Sensing Mattress for Monitoring Sleeping Respiratory

by Wen-Ying Chang, Chien-Chun Huang, Chi-Chun Chen, Chih-Cheng Chang and Chin-Lung Yang

Sensors 2014, 14(11), 22021-22038; https://doi.org/10.3390/s141122021 - 20 Nov 2014

Cited by 19 | Viewed by 8482

Abstract

In this paper, an algorithm to extract respiration signals using a flexible projected capacitive sensing mattress (FPCSM) designed for personal health assessment is proposed. Unlike the interfaces of conventional measurement systems for poly-somnography (PSG) and other alternative contemporary systems, the proposed FPCSM uses [...] Read more.

In this paper, an algorithm to extract respiration signals using a flexible projected capacitive sensing mattress (FPCSM) designed for personal health assessment is proposed. Unlike the interfaces of conventional measurement systems for poly-somnography (PSG) and other alternative contemporary systems, the proposed FPCSM uses projected capacitive sensing capability that is not worn or attached to the body. The FPCSM is composed of a multi-electrode sensor array that can not only observe gestures and motion behaviors, but also enables the FPCSM to function as a respiration monitor during sleep using the proposed approach. To improve long-term monitoring when body movement is possible, the FPCSM enables the selection of data from the sensing array, and the FPCSM methodology selects the electrodes with the optimal signals after the application of a channel reduction algorithm that counts the reversals in the capacitive sensing signals as a quality indicator. The simple algorithm is implemented in the time domain. The FPCSM system is used in experimental tests and is simultaneously compared with a commercial PSG system for verification. Multiple synchronous measurements are performed from different locations of body contact, and parallel data sets are collected. The experimental comparison yields a correlation coefficient of 0.88 between FPCSM and PSG, demonstrating the feasibility of the system design. Full article

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Open AccessArticle

Electrically Insulated Sensing of Respiratory Rate and Heartbeat Using Optical Fibers

by Ernesto Suaste-Gómez, Daniel Hernández-Rivera, Anabel S. Sánchez-Sánchez and Elsy Villarreal-Calva

Sensors 2014, 14(11), 21523-21534; https://doi.org/10.3390/s141121523 - 14 Nov 2014

Cited by 20 | Viewed by 10376

Abstract

Respiratory and heart rates are among the most important physiological parameters used to monitor patients’ health. It is important to design devices that can measure these parameters without risking or altering the subject’s health. In this context, a novel sensing method to monitor [...] Read more.

Respiratory and heart rates are among the most important physiological parameters used to monitor patients’ health. It is important to design devices that can measure these parameters without risking or altering the subject’s health. In this context, a novel sensing method to monitor simultaneously the heartbeat and respiratory rate signals of patients within an electrically safety environment was developed and tested. An optical fiber-based sensor was used in order to detect two optical phenomena. Photo-plethysmography and the relation between bending radius and attenuation of optical fiber were coupled through a single beam light traveling along this fiber. Full article

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Open AccessArticle

PERFORM: A System for Monitoring, Assessment and Management of Patients with Parkinson’s Disease

by Alexandros T. Tzallas, Markos G. Tsipouras, Georgios Rigas, Dimitrios G. Tsalikakis, Evaggelos C. Karvounis, Maria Chondrogiorgi, Fotis Psomadellis, Jorge Cancela, Matteo Pastorino, María Teresa Arredondo Waldmeyer, Spiros Konitsiotis and Dimitrios I. Fotiadis

Sensors 2014, 14(11), 21329-21357; https://doi.org/10.3390/s141121329 - 11 Nov 2014

Cited by 130 | Viewed by 18485

Abstract

In this paper, we describe the PERFORM system for the continuous remote monitoring and management of Parkinson’s disease (PD) patients. The PERFORM system is an intelligent closed-loop system that seamlessly integrates a wide range of wearable sensors constantly monitoring several motor signals of [...] Read more.

In this paper, we describe the PERFORM system for the continuous remote monitoring and management of Parkinson’s disease (PD) patients. The PERFORM system is an intelligent closed-loop system that seamlessly integrates a wide range of wearable sensors constantly monitoring several motor signals of the PD patients. Data acquired are pre-processed by advanced knowledge processing methods, integrated by fusion algorithms to allow health professionals to remotely monitor the overall status of the patients, adjust medication schedules and personalize treatment. The information collected by the sensors (accelerometers and gyroscopes) is processed by several classifiers. As a result, it is possible to evaluate and quantify the PD motor symptoms related to end of dose deterioration (tremor, bradykinesia, freezing of gait (FoG)) as well as those related to over-dose concentration (Levodopa-induced dyskinesia (LID)). Based on this information, together with information derived from tests performed with a virtual reality glove and information about the medication and food intake, a patient specific profile can be built. In addition, the patient specific profile with his evaluation during the last week and last month, is compared to understand whether his status is stable, improving or worsening. Based on that, the system analyses whether a medication change is needed—always under medical supervision—and in this case, information about the medication change proposal is sent to the patient. The performance of the system has been evaluated in real life conditions, the accuracy and acceptability of the system by the PD patients and healthcare professionals has been tested, and a comparison with the standard routine clinical evaluation done by the PD patients’ physician has been carried out. The PERFORM system is used by the PD patients and in a simple and safe non-invasive way for long-term record of their motor status, thus offering to the clinician a precise, long-term and objective view of patient’s motor status and drug/food intake. Thus, with the PERFORM system the clinician can remotely receive precise information for the PD patient’s status on previous days and define the optimal therapeutical treatment. Full article

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Open AccessReview

Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors

by Yueng Santiago Delahoz and Miguel Angel Labrador

Sensors 2014, 14(10), 19806-19842; https://doi.org/10.3390/s141019806 - 22 Oct 2014

Cited by 263 | Viewed by 26601

Abstract

According to nihseniorhealth.gov (a website for older adults), falling represents a great threat as people get older, and providing mechanisms to detect and prevent falls is critical to improve people’s lives. Over 1.6 million U.S. adults are treated for fall-related injuries in emergency [...] Read more.

According to nihseniorhealth.gov (a website for older adults), falling represents a great threat as people get older, and providing mechanisms to detect and prevent falls is critical to improve people’s lives. Over 1.6 million U.S. adults are treated for fall-related injuries in emergency rooms every year suffering fractures, loss of independence, and even death. It is clear then, that this problem must be addressed in a prompt manner, and the use of pervasive computing plays a key role to achieve this. Fall detection (FD) and fall prevention (FP) are research areas that have been active for over a decade, and they both strive for improving people’s lives through the use of pervasive computing. This paper surveys the state of the art in FD and FP systems, including qualitative comparisons among various studies. It aims to serve as a point of reference for future research on the mentioned systems. A general description of FD and FP systems is provided, including the different types of sensors used in both approaches. Challenges and current solutions are presented and described in great detail. A 3-level taxonomy associated with the risk factors of a fall is proposed. Finally, cutting edge FD and FP systems are thoroughly reviewed and qualitatively compared, in terms of design issues and other parameters. Full article

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Open AccessArticle

Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks

by Elena Bergamini, Gabriele Ligorio, Aurora Summa, Giuseppe Vannozzi, Aurelio Cappozzo and Angelo Maria Sabatini

Sensors 2014, 14(10), 18625-18649; https://doi.org/10.3390/s141018625 - 9 Oct 2014

Cited by 203 | Viewed by 13962

Abstract

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic [...] Read more.

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided. Full article

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Open AccessArticle

Synchronous Wearable Wireless Body Sensor Network Composed of Autonomous Textile Nodes

by Peter Vanveerdeghem, Patrick Van Torre, Christiaan Stevens, Jos Knockaert and Hendrik Rogier

Sensors 2014, 14(10), 18583-18610; https://doi.org/10.3390/s141018583 - 9 Oct 2014

Cited by 20 | Viewed by 8670

Abstract

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted [...] Read more.

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system. Full article

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Open AccessArticle

Evaluating Classifiers to Detect Arm Movement Intention from EEG Signals

by Daniel Planelles, Enrique Hortal, Álvaro Costa, Andrés Úbeda, Eduardo Iáez and José M. Azorín

Sensors 2014, 14(10), 18172-18186; https://doi.org/10.3390/s141018172 - 29 Sep 2014

Cited by 39 | Viewed by 8989

Abstract

This paper presents a methodology to detect the intention to make a reaching movement with the arm in healthy subjects before the movement actually starts. This is done by measuring brain activity through electroencephalographic (EEG) signals that are registered by electrodes placed over [...] Read more.

This paper presents a methodology to detect the intention to make a reaching movement with the arm in healthy subjects before the movement actually starts. This is done by measuring brain activity through electroencephalographic (EEG) signals that are registered by electrodes placed over the scalp. The preparation and performance of an arm movement generate a phenomenon called event-related desynchronization (ERD) in the mu and beta frequency bands. A novel methodology to characterize this cognitive process based on three sums of power spectral frequencies involved in ERD is presented. The main objective of this paper is to set the benchmark for classifiers and to choose the most convenient. The best results are obtained using an SVM classifier with around 72% accuracy. This classifier will be used in further research to generate the control commands to move a robotic exoskeleton that helps people suffering from motor disabilities to perform the movement. The final aim is that this brain-controlled robotic exoskeleton improves the current rehabilitation processes of disabled people. Full article

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Open AccessArticle

Novel Wearable and Wireless Ring-Type Pulse Oximeter with Multi-Detectors

by Cheng-Yang Huang, Ming-Che Chan, Chien-Yue Chen and Bor-Shyh Lin

Sensors 2014, 14(9), 17586-17599; https://doi.org/10.3390/s140917586 - 19 Sep 2014

Cited by 41 | Viewed by 11634

Abstract

The pulse oximeter is a popular instrument to monitor the arterial oxygen saturation (SPO₂). Although a fingertip-type pulse oximeter is the mainstream one on the market at present, it is still inconvenient for long-term monitoring, in particular, with respect to motion. [...] Read more.

The pulse oximeter is a popular instrument to monitor the arterial oxygen saturation (SPO₂). Although a fingertip-type pulse oximeter is the mainstream one on the market at present, it is still inconvenient for long-term monitoring, in particular, with respect to motion. Therefore, the development of a wearable pulse oximeter, such as a finger base-type pulse oximeter, can effectively solve the above issue. However, the tissue structure of the finger base is complex, and there is lack of detailed information on the effect of the light source and detector placement on measuring SPO₂. In this study, the practicability of a ring-type pulse oximeter with a multi-detector was investigated by optical human tissue simulation. The optimal design of a ring-type pulse oximeter that can provide the best efficiency of measuring SPO₂ was discussed. The efficiency of ring-type pulse oximeters with a single detector and a multi-detector was also discussed. Finally, a wearable and wireless ring-type pulse oximeter was also implemented to validate the simulation results and was compared with the commercial fingertip-type pulse oximeter. Full article

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Open AccessArticle

Evaluation of Two Approaches for Aligning Data Obtained from a Motion Capture System and an In-Shoe Pressure Measurement System

by Sunwook Kim and Maury A. Nussbaum

Sensors 2014, 14(9), 16994-17007; https://doi.org/10.3390/s140916994 - 12 Sep 2014

Cited by 7 | Viewed by 6583

Abstract

An in-shoe pressure measurement (IPM) system can be used to measure center of pressure (COP) locations, and has fewer restrictions compared to the more conventional approach using a force platform. The insole of an IPM system, however, has its own coordinate system. To [...] Read more.

An in-shoe pressure measurement (IPM) system can be used to measure center of pressure (COP) locations, and has fewer restrictions compared to the more conventional approach using a force platform. The insole of an IPM system, however, has its own coordinate system. To use an IPM system along with a motion capture system, there is thus a need to align the coordinate systems of the two measurement systems. To address this need, the current study examined two different approaches—rigid body transformation and nonlinear mapping (i.e., multilayer feed-forward neural network (MFNN))—to express COP measurements from an IPM system in the coordinate system of a motion capture system. Ten participants (five male and five female) completed several simulated manual material handling (MMH) activities, and during these activities the performance of the two approaches was assessed. Results indicated that: (1) performance varied between MMH activity types; and (2) a MFNN performed better than or comparable to the rigid body transformation, depending on the specific input variable sets used. Further, based on the results obtained, it was argued that a nonlinear mapping vs. rigid body transformation approach may be more effective to account for shoe deformation during MMH or potentially other types of physical activity. Full article

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Open AccessArticle

DIMETER: A Haptic Master Device for Tremor Diagnosis in Neurodegenerative Diseases

by Roberto González, Antonio Barrientos, Jaime Del Cerro and Benito Coca

Sensors 2014, 14(3), 4536-4559; https://doi.org/10.3390/s140304536 - 7 Mar 2014

Cited by 6 | Viewed by 8271

Abstract

In this study, a device based on patient motion capture is developed for the reliable and non-invasive diagnosis of neurodegenerative diseases. The primary objective of this study is the classification of differential diagnosis between Parkinson's disease (PD) and essential tremor (ET). The DIMETER [...] Read more.

In this study, a device based on patient motion capture is developed for the reliable and non-invasive diagnosis of neurodegenerative diseases. The primary objective of this study is the classification of differential diagnosis between Parkinson's disease (PD) and essential tremor (ET). The DIMETER system has been used in the diagnoses of a significant number of patients at two medical centers in Spain. Research studies on classification have primarily focused on the use of well-known and reliable diagnosis criteria developed by qualified personnel. Here, we first present a literature review of the methods used to detect and evaluate tremor; then, we describe the DIMETER device in terms of the software and hardware used and the battery of tests developed to obtain the best diagnoses. All of the tests are classified and described in terms of the characteristics of the data obtained. A list of parameters obtained from the tests is provided, and the results obtained using multilayer perceptron (MLP) neural networks are presented and analyzed. Full article

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Open AccessArticle

Towards Whole Body Fatigue Assessment of Human Movement: A Fatigue-Tracking System Based on Combined sEMG and Accelerometer Signals

by Haiwei Dong, Izaskun Ugalde, Nadia Figueroa and Abdulmotaleb El Saddik

Sensors 2014, 14(2), 2052-2070; https://doi.org/10.3390/s140202052 - 27 Jan 2014

Cited by 30 | Viewed by 11235

Abstract

This paper proposes a method to assess the overall fatigue of human body movement. First of all, according to previous research regarding localized muscular fatigue, a linear relation is assumed between the mean frequency and the muscular working time when the muscle is [...] Read more.

This paper proposes a method to assess the overall fatigue of human body movement. First of all, according to previous research regarding localized muscular fatigue, a linear relation is assumed between the mean frequency and the muscular working time when the muscle is experiencing fatigue. This assumption is verified with a rigorous statistical analysis. Based on this proven linearity, localized muscular fatigue is simplified as a linear model. Furthermore, localized muscular fatigue is considered a dynamic process and, hence, the localized fatigue levels are tracked by updating the parameters with the most current surface electromyogram (sEMG) measurements. Finally, an overall fatigue level is computed by fusing localized muscular fatigue levels. The developed fatigue-tracking system is evaluated with two fatigue experiments (in which 10 male subjects and seven female subjects participated), including holding self-weight (dip start position training) and lifting weight with one arm (arm curl training). Full article

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Graphical abstract

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Open AccessArticle

Energy-Efficient Data Reduction Techniques for Wireless Seizure Detection Systems

by Joyce Chiang and Rabab K. Ward

Sensors 2014, 14(2), 2036-2051; https://doi.org/10.3390/s140202036 - 24 Jan 2014

Cited by 32 | Viewed by 7136

Abstract

The emergence of wireless sensor networks (WSNs) has motivated a paradigm shift in patient monitoring and disease control. Epilepsy management is one of the areas that could especially benefit from the use of WSN. By using miniaturized wireless electroencephalogram (EEG) sensors, it is [...] Read more.

The emergence of wireless sensor networks (WSNs) has motivated a paradigm shift in patient monitoring and disease control. Epilepsy management is one of the areas that could especially benefit from the use of WSN. By using miniaturized wireless electroencephalogram (EEG) sensors, it is possible to perform ambulatory EEG recording and real-time seizure detection outside clinical settings. One major consideration in using such a wireless EEG-based system is the stringent battery energy constraint at the sensor side. Different solutions to reduce the power consumption at this side are therefore highly desired. The conventional approach incurs a high power consumption, as it transmits the entire EEG signals wirelessly to an external data server (where seizure detection is carried out). This paper examines the use of data reduction techniques for reducing the amount of data that has to be transmitted and, thereby, reducing the required power consumption at the sensor side. Two data reduction approaches are examined: compressive sensing-based EEG compression and low-complexity feature extraction. Their performance is evaluated in terms of seizure detection effectiveness and power consumption. Experimental results show that by performing low-complexity feature extraction at the sensor side and transmitting only the features that are pertinent to seizure detection to the server, a considerable overall saving in power is achieved. The battery life of the system is increased by 14 times, while the same seizure detection rate as the conventional approach (95%) is maintained. Full article

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Open AccessArticle

An Energy Efficient Compressed Sensing Framework for the Compression of Electroencephalogram Signals

by Simon Fauvel and Rabab K. Ward

Sensors 2014, 14(1), 1474-1496; https://doi.org/10.3390/s140101474 - 15 Jan 2014

Cited by 43 | Viewed by 9408

Abstract

The use of wireless body sensor networks is gaining popularity in monitoring and communicating information about a person’s health. In such applications, the amount of data transmitted by the sensor node should be minimized. This is because the energy available in these battery [...] Read more.

The use of wireless body sensor networks is gaining popularity in monitoring and communicating information about a person’s health. In such applications, the amount of data transmitted by the sensor node should be minimized. This is because the energy available in these battery powered sensors is limited. In this paper, we study the wireless transmission of electroencephalogram (EEG) signals. We propose the use of a compressed sensing (CS) framework to efficiently compress these signals at the sensor node. Our framework exploits both the temporal correlation within EEG signals and the spatial correlations amongst the EEG channels. We show that our framework is up to eight times more energy efficient than the typical wavelet compression method in terms of compression and encoding computations and wireless transmission. We also show that for a fixed compression ratio, our method achieves a better reconstruction quality than the CS-based state-of-the art method. We finally demonstrate that our method is robust to measurement noise and to packet loss and that it is applicable to a wide range of EEG signal types. Full article

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Open AccessArticle

A New Calibration Methodology for Thorax and Upper Limbs Motion Capture in Children Using Magneto and Inertial Sensors

by Luca Ricci, Domenico Formica, Laura Sparaci, Francesca Romana Lasorsa, Fabrizio Taffoni, Eleonora Tamilia and Eugenio Guglielmelli

Sensors 2014, 14(1), 1057-1072; https://doi.org/10.3390/s140101057 - 9 Jan 2014

Cited by 41 | Viewed by 11671

Abstract

Recent advances in wearable sensor technologies for motion capture have produced devices, mainly based on magneto and inertial measurement units (M-IMU), that are now suitable for out-of-the-lab use with children. In fact, the reduced size, weight and the wireless connectivity meet the requirement [...] Read more.

Recent advances in wearable sensor technologies for motion capture have produced devices, mainly based on magneto and inertial measurement units (M-IMU), that are now suitable for out-of-the-lab use with children. In fact, the reduced size, weight and the wireless connectivity meet the requirement of minimum obtrusivity and give scientists the possibility to analyze children’s motion in daily life contexts. Typical use of magneto and inertial measurement units (M-IMU) motion capture systems is based on attaching a sensing unit to each body segment of interest. The correct use of this setup requires a specific calibration methodology that allows mapping measurements from the sensors’ frames of reference into useful kinematic information in the human limbs’ frames of reference. The present work addresses this specific issue, presenting a calibration protocol to capture the kinematics of the upper limbs and thorax in typically developing (TD) children. The proposed method allows the construction, on each body segment, of a meaningful system of coordinates that are representative of real physiological motions and that are referred to as functional frames (FFs). We will also present a novel cost function for the Levenberg–Marquardt algorithm, to retrieve the rotation matrices between each sensor frame (SF) and the corresponding FF. Reported results on a group of 40 children suggest that the method is repeatable and reliable, opening the way to the extensive use of this technology for out-of-the-lab motion capture in children. Full article

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Open AccessReview

Technological Solutions and Main Indices for the Assessment of Newborns’ Nutritive Sucking: A Review

by Eleonora Tamilia, Fabrizio Taffoni, Domenico Formica, Luca Ricci, Emiliano Schena, Flavio Keller and Eugenio Guglielmelli

Sensors 2014, 14(1), 634-658; https://doi.org/10.3390/s140100634 - 2 Jan 2014

Cited by 38 | Viewed by 11934

Abstract

Nutritive Sucking (NS) is a highly organized process that is essential for infants’ feeding during the first six months of their life. It requires the complex coordination of sucking, swallowing and breathing. The infant’s inability to perform a safe and successful oral feeding [...] Read more.

Nutritive Sucking (NS) is a highly organized process that is essential for infants’ feeding during the first six months of their life. It requires the complex coordination of sucking, swallowing and breathing. The infant’s inability to perform a safe and successful oral feeding can be an early detector of immaturity of the Central Nervous System (CNS). Even though the importance of early sucking measures has been confirmed over the years, the need for standardized instrumental assessment tools still exists. Clinicians would benefit from specifically designed devices to assess oral feeding ability in their routine clinical monitoring and decision-making process. This work is a review of the main instrumental solutions developed to assess an infant’s NS behavior, with a detailed survey of the main quantities and indices measured and/or estimated to characterize sucking behavior skills and their development. The adopted sensing measuring systems will be described, and their main advantages and weaknesses will be discussed, taking into account their application to clinical practice, or to at-home monitoring as post-discharge assessment tools. Finally, the study will highlight the most suitable sensing solutions and give some prompts for further research. Full article

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Open AccessArticle

On the Capability of Smartphones to Perform as Communication Gateways in Medical Wireless Personal Area Networks

by María José Morón, Rafael Luque and Eduardo Casilari

Sensors 2014, 14(1), 575-594; https://doi.org/10.3390/s140100575 - 2 Jan 2014

Cited by 37 | Viewed by 10643

Abstract

This paper evaluates and characterizes the technical performance of medical wireless personal area networks (WPANs) that are based on smartphones. For this purpose, a prototype of a health telemonitoring system is presented. The prototype incorporates a commercial Android smartphone, which acts as a [...] Read more.

This paper evaluates and characterizes the technical performance of medical wireless personal area networks (WPANs) that are based on smartphones. For this purpose, a prototype of a health telemonitoring system is presented. The prototype incorporates a commercial Android smartphone, which acts as a relay point, or “gateway”, between a set of wireless medical sensors and a data server. Additionally, the paper investigates if the conventional capabilities of current commercial smartphones can be affected by their useas gateways or “Holters” in health monitoring applications. Specifically, the profiling has focused on the CPU and power consumption of the mobile devices. These metrics have been measured under several test conditions modifying the smartphone model, the type of sensors connected to the WPAN, the employed Bluetooth profile (SPP (serial port profile) or HDP (health device profile)), the use of other peripherals, such as a GPS receiver, the impact of the use of the Wi-Fi interface or the employed method to encode and forward the data that are collected from the sensors. Full article

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2013

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Open AccessArticle

A Modular Sensorized Mat for Monitoring Infant Posture

by Marco Donati, Francesca Cecchi, Filippo Bonaccorso, Marco Branciforte, Paolo Dario and Nicola Vitiello

Sensors 2014, 14(1), 510-531; https://doi.org/10.3390/s140100510 - 31 Dec 2013

Cited by 26 | Viewed by 9159

Abstract

We present a novel sensorized mat for monitoring infant’s posture through the measure of pressure maps. The pressure-sensitive mat is based on an optoelectronic technology developed in the last few years at Scuola Superiore Sant’Anna: a soft silicone skin cover, which constitutes the [...] Read more.

We present a novel sensorized mat for monitoring infant’s posture through the measure of pressure maps. The pressure-sensitive mat is based on an optoelectronic technology developed in the last few years at Scuola Superiore Sant’Anna: a soft silicone skin cover, which constitutes the mat, participates in the transduction principle and provides the mat with compliance. The device has a modular structure (with a minimum of one and a maximum of six sub-modules, and a total surface area of about 1 m²) that enables dimensional adaptation of the pressure-sensitive area to different specific applications. The system consists of on-board electronics for data collection, pre-elaboration, and transmission to a remote computing unit for analysis and posture classification. In this work we present a complete description of the sensing apparatus along with its experimental characterization and validation with five healthy infants. Full article

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Open AccessArticle

A Novel Assessment of Flexibility by Microcirculatory Signals

by Jian-Guo Bau, Taipau Chia, Yu-Fang Chung, Kun-Hao Chen and Shyi-Kuen Wu

Sensors 2014, 14(1), 478-491; https://doi.org/10.3390/s140100478 - 30 Dec 2013

Cited by 4 | Viewed by 6877

Abstract

Flexibility testing is one of the most important fitness assessments. It is generally evaluated by measuring the range of motion (RoM) of body segments around a joint center. This study presents a novel assessment of flexibility in the microcirculatory aspect. Eighteen college students [...] Read more.

Flexibility testing is one of the most important fitness assessments. It is generally evaluated by measuring the range of motion (RoM) of body segments around a joint center. This study presents a novel assessment of flexibility in the microcirculatory aspect. Eighteen college students were recruited for the flexibility assessment. The flexibility of the leg was defined according to the angle of active ankle dorsiflexion measured by goniometry. Six legs were excluded, and the remaining thirty legs were categorized into two groups, group H (n = 15 with higher flexibility) and group L (n = 15 with lower flexibility), according to their RoM. The microcirculatory signals of the gastrocnemius muscle on the belly were monitored by using Laser-Doppler Flowmetry (LDF) with a noninvasive skin probe. Three indices of nonpulsatile component (DC), pulsatile component (AC) and perfusion pulsatility (PP) were defined from the LDF signals after signal processing. The results revealed that both the DC and AC values of the group H that demonstrated higher stability underwent muscle stretching. In contrast, these indices of group L had interferences and became unstable during muscle stretching. The PP value of group H was a little higher than that of group L. These primary findings help us to understand the microcirculatory physiology of flexibility, and warrant further investigations for use of non-invasive LDF techniques in the assessment of flexibility. Full article

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Open AccessReview

Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges

by Hadi Banaee, Mobyen Uddin Ahmed and Amy Loutfi

Sensors 2013, 13(12), 17472-17500; https://doi.org/10.3390/s131217472 - 17 Dec 2013

Cited by 341 | Viewed by 39833

Abstract

The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to [...] Read more.

The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems. Full article

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Open AccessArticle

Combined Hand Gesture — Speech Model for Human Action Recognition

by Sheng-Tzong Cheng, Chih-Wei Hsu and Jian-Pan Li

Sensors 2013, 13(12), 17098-17129; https://doi.org/10.3390/s131217098 - 12 Dec 2013

Cited by 11 | Viewed by 9801

Abstract

This study proposes a dynamic hand gesture detection technology to effectively detect dynamic hand gesture areas, and a hand gesture recognition technology to improve the dynamic hand gesture recognition rate. Meanwhile, the corresponding relationship between state sequences in hand gesture and speech models [...] Read more.

This study proposes a dynamic hand gesture detection technology to effectively detect dynamic hand gesture areas, and a hand gesture recognition technology to improve the dynamic hand gesture recognition rate. Meanwhile, the corresponding relationship between state sequences in hand gesture and speech models is considered by integrating speech recognition technology with a multimodal model, thus improving the accuracy of human behavior recognition. The experimental results proved that the proposed method can effectively improve human behavior recognition accuracy and the feasibility of system applications. Experimental results verified that the multimodal gesture-speech model provided superior accuracy when compared to the single modal versions. Full article

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Open AccessArticle

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

by Mau-Tsuen Yang and Min-Wen Chuang

Sensors 2013, 13(12), 16985-17005; https://doi.org/10.3390/s131216985 - 10 Dec 2013

Cited by 10 | Viewed by 8839

Abstract

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at [...] Read more.

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. Full article

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870 KiB

Open AccessArticle

Automatic and Objective Assessment of Alternating Tapping Performance in Parkinson’s Disease

by Mevludin Memedi, Taha Khan, Peter Grenholm, Dag Nyholm and Jerker Westin

Sensors 2013, 13(12), 16965-16984; https://doi.org/10.3390/s131216965 - 9 Dec 2013

Cited by 33 | Viewed by 9272

Abstract

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad [...] Read more.

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping. Full article

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550 KiB

Open AccessArticle

Design and Evaluation of a Low-Cost Smartphone Pulse Oximeter

by Christian L. Petersen, Tso P. Chen, J. Mark Ansermino and Guy A. Dumont

Sensors 2013, 13(12), 16882-16893; https://doi.org/10.3390/s131216882 - 6 Dec 2013

Cited by 55 | Viewed by 18281

Abstract

Infectious diseases such as pneumonia take the lives of millions of children in low- and middle-income countries every year. Many of these deaths could be prevented with the availability of robust and low-cost diagnostic tools using integrated sensor technology. Pulse oximetry in particular, [...] Read more.

Infectious diseases such as pneumonia take the lives of millions of children in low- and middle-income countries every year. Many of these deaths could be prevented with the availability of robust and low-cost diagnostic tools using integrated sensor technology. Pulse oximetry in particular, offers a unique non-invasive and specific test for an increase in the severity of many infectious diseases such as pneumonia. If pulse oximetry could be delivered on widely available mobile phones, it could become a compelling solution to global health challenges. Many lives could be saved if this technology was disseminated effectively in the affected regions of the world to rescue patients from the fatal consequences of these infectious diseases. We describe the implementation of such an oximeter that interfaces a conventional clinical oximeter finger sensor with a smartphone through the headset jack audio interface, and present a simulator-based systematic verification system to be used for automated validation of the sensor interface on different smartphones and media players. An excellent agreement was found between the simulator and the audio oximeter for both oxygen saturation and heart rate over a wide range of optical transmission levels on 4th and 5th generations of the iPod Touch^TM and iPhone^TM devices. Full article

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2948 KiB

Open AccessArticle

Assessment and Certification of Neonatal Incubator Sensors through an Inferential Neural Network

by José Medeiros De Araújo, Júnior, José Maria Pires De Menezes, Júnior, Alberto Alexandre Moura de Albuquerque, Otacílio Da Mota Almeida and Fábio Meneghetti Ugulino de Araújo

Sensors 2013, 13(11), 15613-15632; https://doi.org/10.3390/s131115613 - 15 Nov 2013

Cited by 11 | Viewed by 14491

Abstract

Measurement and diagnostic systems based on electronic sensors have been increasingly essential in the standardization of hospital equipment. The technical standard IEC (International Electrotechnical Commission) 60601-2-19 establishes requirements for neonatal incubators and specifies the calibration procedure and validation tests for such devices using [...] Read more.

Measurement and diagnostic systems based on electronic sensors have been increasingly essential in the standardization of hospital equipment. The technical standard IEC (International Electrotechnical Commission) 60601-2-19 establishes requirements for neonatal incubators and specifies the calibration procedure and validation tests for such devices using sensors systems. This paper proposes a new procedure based on an inferential neural network to evaluate and calibrate a neonatal incubator. The proposal presents significant advantages over the standard calibration process, i.e., the number of sensors is drastically reduced, and it runs with the incubator under operation. Since the sensors used in the new calibration process are already installed in the commercial incubator, no additional hardware is necessary; and the calibration necessity can be diagnosed in real time without the presence of technical professionals in the neonatal intensive care unit (NICU). Experimental tests involving the aforementioned calibration system are carried out in a commercial incubator in order to validate the proposal. Full article

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1396 KiB

Open AccessReview

Design and Test of a Hybrid Foot Force Sensing and GPS System for Richer User Mobility Activity Recognition

by Zelun Zhang and Stefan Poslad

Sensors 2013, 13(11), 14918-14953; https://doi.org/10.3390/s131114918 - 1 Nov 2013

Cited by 7 | Viewed by 9107

Abstract

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) [...] Read more.

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals. Full article

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193 KiB

Open AccessArticle

Comparison of Systolic Blood Pressure Values Obtained by Photoplethysmography and by Korotkoff Sounds

by Meir Nitzan, Yair Adar, Ellie Hoffman, Eran Shalom, Shlomo Engelberg, Iddo Z. Ben-Dov and Michael Bursztyn

Sensors 2013, 13(11), 14797-14812; https://doi.org/10.3390/s131114797 - 31 Oct 2013

Cited by 21 | Viewed by 10881

Abstract

In the current study, a non-invasive technique for systolic blood pressure (SBP) measurement based on the detection of photoplethysmographic (PPG) pulses during pressure-cuff deflation was compared to sphygmomanometry—the Korotkoff sounds technique. The PPG pulses disappear for cuff-pressures above the SBP value and reappear [...] Read more.

In the current study, a non-invasive technique for systolic blood pressure (SBP) measurement based on the detection of photoplethysmographic (PPG) pulses during pressure-cuff deflation was compared to sphygmomanometry—the Korotkoff sounds technique. The PPG pulses disappear for cuff-pressures above the SBP value and reappear when the cuff-pressure decreases below the SBP value. One hundred and twenty examinations were performed on forty subjects. In 97 examinations the two methods differed by less than 3 mmHg. In nine examinations the SBP value measured by PPG was higher than that measured by sphygmomanometry by 5 mmHg or more. In only one examination the former was lower by 5 mmHg or more than the latter. The appearance of either the PPG pulses or the Korotkoff sounds assures that the artery under the cuff is open during systolic peak pressure. In the nine examinations mentioned above the PPG pulses were observed while Korotkoff sounds were not detected, despite the open artery during systole. In these examinations, the PPG-based technique was more reliable than sphygmomanometry. The high signal-to-noise ratio of measured PPG pulses indicates that automatic measurement of the SBP by means of automatic detection of the PPG signals is feasible. Full article

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464 KiB

Open AccessArticle

A Wearable Inertial Measurement Unit for Long-Term Monitoring in the Dependency Care Area

by Daniel Rodríguez-Martín, Carlos Pérez-López, Albert Samà, Joan Cabestany and Andreu Català

Sensors 2013, 13(10), 14079-14104; https://doi.org/10.3390/s131014079 - 18 Oct 2013

Cited by 63 | Viewed by 15655

Abstract

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with [...] Read more.

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU’s movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A µSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson’s disease symptoms, in gait analysis, and in a fall detection system. Full article

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476 KiB

Open AccessArticle

On Using Maximum a Posteriori Probability Based on a Bayesian Model for Oscillometric Blood Pressure Estimation

by Soojeong Lee, Gwanggil Jeon and Gangseong Lee

Sensors 2013, 13(10), 13609-13623; https://doi.org/10.3390/s131013609 - 10 Oct 2013

Cited by 10 | Viewed by 8431

Abstract

The maximum amplitude algorithm (MAA) is generally utilized in the estimation of the pressure values, and it uses heuristically obtained ratios of systolic and diastolic oscillometric amplitude to the mean arterial pressure (known as systolic and diastolic ratios) in order to estimate the [...] Read more.

The maximum amplitude algorithm (MAA) is generally utilized in the estimation of the pressure values, and it uses heuristically obtained ratios of systolic and diastolic oscillometric amplitude to the mean arterial pressure (known as systolic and diastolic ratios) in order to estimate the systolic and diastolic pressures. This paper proposes a Bayesian model to estimate the systolic and diastolic ratios. These ratios are an improvement over the single fixed systolic and diastolic ratios used in the algorithms that are available in the literature. The proposed method shows lower mean difference (MD) with standard deviation (SD) compared to the MAA for both SBP and DBP consistently in all the five measurements. Full article

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367 KiB

Open AccessCommunication

Autonomic Nervous System Responses Can Reveal Visual Fatigue Induced by 3D Displays

by Chi Jung Kim, Sangin Park, Myeung Ju Won, Mincheol Whang and Eui Chul Lee

Sensors 2013, 13(10), 13054-13062; https://doi.org/10.3390/s131013054 - 26 Sep 2013

Cited by 37 | Viewed by 8148

Abstract

Previous research has indicated that viewing 3D displays may induce greater visual fatigue than viewing 2D displays. Whether viewing 3D displays can evoke measureable emotional responses, however, is uncertain. In the present study, we examined autonomic nervous system responses in subjects viewing 2D [...] Read more.

Previous research has indicated that viewing 3D displays may induce greater visual fatigue than viewing 2D displays. Whether viewing 3D displays can evoke measureable emotional responses, however, is uncertain. In the present study, we examined autonomic nervous system responses in subjects viewing 2D or 3D displays. Autonomic responses were quantified in each subject by heart rate, galvanic skin response, and skin temperature. Viewers of both 2D and 3D displays showed strong positive correlations with heart rate, which indicated little differences between groups. In contrast, galvanic skin response and skin temperature showed weak positive correlations with average difference between viewing 2D and 3D. We suggest that galvanic skin response and skin temperature can be used to measure and compare autonomic nervous responses in subjects viewing 2D and 3D displays. Full article

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962 KiB

Open AccessReview

Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations

by Rinat Khusainov, Djamel Azzi, Ifeyinwa E. Achumba and Sebastian D. Bersch

Sensors 2013, 13(10), 12852-12902; https://doi.org/10.3390/s131012852 - 25 Sep 2013

Cited by 143 | Viewed by 14140

Abstract

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation [...] Read more.

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions. Full article

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2117 KiB

Open AccessArticle

Laser Doppler Blood Flow Imaging Using a CMOS Imaging Sensor with On-Chip Signal Processing

by Diwei He, Hoang C. Nguyen, Barrie R. Hayes-Gill, Yiqun Zhu, John A. Crowe, Cally Gill, Geraldine F. Clough and Stephen P. Morgan

Sensors 2013, 13(9), 12632-12647; https://doi.org/10.3390/s130912632 - 18 Sep 2013

Cited by 17 | Viewed by 11822

Abstract

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used [...] Read more.

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue. Full article

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878 KiB

Open AccessCommunication

The Capability of Fiber Bragg Grating Sensors to Measure Amputees’ Trans-Tibial Stump/Socket Interface Pressures

by Ebrahim A. Al-Fakih, Noor Azuan Abu Osman, Arezoo Eshraghi and Faisal Rafiq Mahamd Adikan

Sensors 2013, 13(8), 10348-10357; https://doi.org/10.3390/s130810348 - 12 Aug 2013

Cited by 29 | Viewed by 9489

Abstract

This study presents the first investigation into the capability of fiber Bragg grating (FBG) sensors to measure interface pressure between the stump and the prosthetic sockets of a trans-tibial amputee. FBG element(s) were recoated with and embedded in a thin layer of epoxy [...] Read more.

This study presents the first investigation into the capability of fiber Bragg grating (FBG) sensors to measure interface pressure between the stump and the prosthetic sockets of a trans-tibial amputee. FBG element(s) were recoated with and embedded in a thin layer of epoxy material to form a sensing pad, which was in turn embedded in a silicone polymer material to form a pressure sensor. The sensor was tested in real time by inserting a heavy-duty balloon into the socket and inflating it by using an air compressor. This test was conducted to examine the sensitivity and repeatability of the sensor when subjected to pressure from the stump of the trans-tibial amputee and to mimic the actual environment of the amputee’s Patellar Tendon (PT) bar. The sensor exhibited a sensitivity of 127 pm/N and a maximum FSO hysteresis of around ~0.09 in real-time operation. Very good reliability was achieved when the sensor was utilized for in situ measurements. This study may lead to smart FBG-based amputee stump/socket structures for pressure monitoring in amputee socket systems, which will result in better-designed prosthetic sockets that ensure improved patient satisfaction. Full article

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17714 KiB

Open AccessArticle

Design of a Wearable Sensing System for Human Motion Monitoring in Physical Rehabilitation

by Lara González-Villanueva, Stefano Cagnoni and Luca Ascari

Sensors 2013, 13(6), 7735-7755; https://doi.org/10.3390/s130607735 - 17 Jun 2013

Cited by 34 | Viewed by 11108

Abstract

Human motion monitoring and analysis can be an essential part of a wide spectrum of applications, including physical rehabilitation among other potential areas of interest. Creating non-invasive systems for monitoring patients while performing rehabilitation exercises, to provide them with an objective feedback, is [...] Read more.

Human motion monitoring and analysis can be an essential part of a wide spectrum of applications, including physical rehabilitation among other potential areas of interest. Creating non-invasive systems for monitoring patients while performing rehabilitation exercises, to provide them with an objective feedback, is one of the current challenges. In this paper we present a wearable multi-sensor system for human motion monitoring, which has been developed for use in rehabilitation. It is composed of a number of small modules that embed high-precision accelerometers and wireless communications to transmit the information related to the body motion to an acquisition device. The results of a set of experiments we made to assess its performance in real-world setups demonstrate its usefulness in human motion acquisition and tracking, as required, for example, in activity recognition, physical/athletic performance evaluation and rehabilitation. Full article

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Graphical abstract

482 KiB

Open AccessArticle

Soft Stethoscope for Detecting Asthma Wheeze in Young Children

by Chun Yu, Tzu-Hsiu Tsai, Shi-Ing Huang and Chii-Wann Lin

Sensors 2013, 13(6), 7399-7413; https://doi.org/10.3390/s130607399 - 6 Jun 2013

Cited by 23 | Viewed by 10376

Abstract

Asthma is a chronic disease that is commonly suffered by children. Asthmatic children have a lower quality of life than other children. Physicians and pediatricians recommend that parents record the frequency of attacks and their symptoms to help manage their children’s asthma. However, [...] Read more.

Asthma is a chronic disease that is commonly suffered by children. Asthmatic children have a lower quality of life than other children. Physicians and pediatricians recommend that parents record the frequency of attacks and their symptoms to help manage their children’s asthma. However, the lack of a convenient device for monitoring the asthmatic condition leads to the difficulties in managing it, especially when it is suffered by young children. This work develops a wheeze detection system for use at home. A small and soft stethoscope was used to collect the respiratory sound. The wheeze detection algorithm was the Adaptive Respiratory Spectrum Correlation Coefficient (RSACC) algorithm, which has the advantages of high sensitivity/specificity and a low computational requirement. Fifty-nine sound files from eight young children (one to seven years old) were collected in the emergency room and analyzed. The results revealed that the system provided 88% sensitivity and 94% specificity in wheeze detection. In conclusion, this small soft stethoscope can be easily used on young children. A noisy environment does not affect the effectiveness of the system in detecting wheeze. Hence, the system can be used at home by parents who wish to evaluate and manage the asthmatic condition of their children. Full article

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