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16 pages, 3815 KiB

Open AccessArticle

Change-Point Detection of Peak Tibial Acceleration in Overground Running Retraining

by Pieter Van den Berghe, Maxim Gosseries, Joeri Gerlo, Matthieu Lenoir, Marc Leman and Dirk De Clercq

Sensors 2020, 20(6), 1720; https://doi.org/10.3390/s20061720 - 19 Mar 2020

Cited by 13 | Viewed by 5191

Abstract

A method is presented for detecting changes in the axial peak tibial acceleration while adapting to self-discovered lower-impact running. Ten runners with high peak tibial acceleration were equipped with a wearable auditory biofeedback system. They ran on an athletic track without and with [...] Read more.

A method is presented for detecting changes in the axial peak tibial acceleration while adapting to self-discovered lower-impact running. Ten runners with high peak tibial acceleration were equipped with a wearable auditory biofeedback system. They ran on an athletic track without and with real-time auditory biofeedback at the instructed speed of 3.2 m·s⁻¹. Because inter-subject variation may underline the importance of individualized retraining, a change-point analysis was used for each subject. The tuned change-point application detected major and subtle changes in the time series. No changes were found in the no-biofeedback condition. In the biofeedback condition, a first change in the axial peak tibial acceleration occurred on average after 309 running gait cycles (3′40″). The major change was a mean reduction of 2.45 g which occurred after 699 running gait cycles (8′04″) in this group. The time needed to achieve the major reduction varied considerably between subjects. Because of the individualized approach to gait retraining and its relatively quick response due to a strong sensorimotor coupling, we want to highlight the potential of a stand-alone biofeedback system that provides real-time, continuous, and auditory feedback in response to the axial peak tibial acceleration for lower-impact running. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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14 pages, 9842 KiB

Open AccessArticle

Monitoring the Heavy Metal Lead Inside Living Drosophila with a FRET-Based Biosensor

by De-Ming Yang, Robeth Viktoria Manurung, Yu-Syuan Lin, Tai-Yu Chiu, Wei-Qun Lai, Yu-Fen Chang and Tsai-Feng Fu

Sensors 2020, 20(6), 1712; https://doi.org/10.3390/s20061712 - 19 Mar 2020

Cited by 8 | Viewed by 5057

Abstract

The harmful impact of the heavy metal lead on human health has been known for years. However, materials that contain lead remain in the environment. Measuring the blood lead level (BLL) is the only way to officially evaluate the degree of exposure to [...] Read more.

The harmful impact of the heavy metal lead on human health has been known for years. However, materials that contain lead remain in the environment. Measuring the blood lead level (BLL) is the only way to officially evaluate the degree of exposure to lead. The so-called “safe value” of the BLL seems to unreliably represent the secure threshold for children. In general, lead’s underlying toxicological mechanism remains unclear and needs to be elucidated. Therefore, we developed a novel genetically encoded fluorescence resonance energy transfer (FRET)-based lead biosensor, Met-lead, and applied it to transgenic Drosophila to perform further investigations. We combined Met-lead with the UAS-GAL4 system to the sensor protein specifically expressed within certain regions of fly brains. Using a suitable imaging platform, including a fast epifluorescent or confocal laser-scanning/two-photon microscope with high resolution, we recorded the changes in lead content inside fly brains ex vivo and in vivo and at different life stages. The blood–brain barrier was found to play an important role in the protection of neurons in the brain against damage due to the heavy metal lead, either through food or microinjection into the abdomen. Met-lead has the potential to be a powerful tool for the sensing of lead within living organisms by employing either a fast epi-FRET microscope or high-resolution brain imaging. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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28 pages, 7120 KiB

Open AccessArticle

Electronic Skin Wearable Sensors for Detecting Lumbar–Pelvic Movements

by Yuxin Zhang, Pari Delir Haghighi, Frada Burstein, Lim Wei Yap, Wenlong Cheng, Lina Yao and Flavia Cicuttini

Sensors 2020, 20(5), 1510; https://doi.org/10.3390/s20051510 - 9 Mar 2020

Cited by 24 | Viewed by 7091

Abstract

Background: A nanomaterial-based electronic-skin (E-Skin) wearable sensor has been successfully used for detecting and measuring body movements such as finger movement and foot pressure. The ultrathin and highly sensitive characteristics of E-Skin sensor make it a suitable alternative for continuously out-of-hospital lumbar–pelvic movement [...] Read more.

Background: A nanomaterial-based electronic-skin (E-Skin) wearable sensor has been successfully used for detecting and measuring body movements such as finger movement and foot pressure. The ultrathin and highly sensitive characteristics of E-Skin sensor make it a suitable alternative for continuously out-of-hospital lumbar–pelvic movement (LPM) monitoring. Monitoring these movements can help medical experts better understand individuals’ low back pain experience. However, there is a lack of prior studies in this research area. Therefore, this paper explores the potential of E-Skin sensors to detect and measure the anatomical angles of lumbar–pelvic movements by building a linear relationship model to compare its performance to clinically validated inertial measurement unit (IMU)-based sensing system (ViMove). Methods: The paper first presents a review and classification of existing wireless sensing technologies for monitoring of body movements, and then it describes a series of experiments performed with E-Skin sensors for detecting five standard LPMs including flexion, extension, pelvic tilt, lateral flexion, and rotation, and measure their anatomical angles. The outputs of both E-Skin and ViMove sensors were recorded during each experiment and further analysed to build the comparative models to evaluate the performance of detecting and measuring LPMs. Results: E-Skin sensor outputs showed a persistently repeating pattern for each movement. Due to the ability to sense minor skin deformation by E-skin sensor, its reaction time in detecting lumbar–pelvic movement is quicker than ViMove by ~1 s. Conclusions: E-Skin sensors offer new capabilities for detecting and measuring lumbar–pelvic movements. They have lower cost compared to commercially available IMU-based systems and their non-invasive highly stretchable characteristic makes them more comfortable for long-term use. These features make them a suitable sensing technology for developing continuous, out-of-hospital real-time monitoring and management systems for individuals with low back pain. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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19 pages, 572 KiB

Open AccessArticle

Combination of Sensor Data and Health Monitoring for Early Detection of Subclinical Ketosis in Dairy Cows

by Valentin Sturm, Dmitry Efrosinin, Manfred Öhlschuster, Erika Gusterer, Marc Drillich and Michael Iwersen

Sensors 2020, 20(5), 1484; https://doi.org/10.3390/s20051484 - 8 Mar 2020

Cited by 20 | Viewed by 4136

Abstract

Subclinical ketosis is a metabolic disease in early lactation. It contributes to economic losses because of reduced milk yield and may promote the development of secondary diseases. Thus, an early detection seems desirable as it enables the farmer to initiate countermeasures. To support [...] Read more.

Subclinical ketosis is a metabolic disease in early lactation. It contributes to economic losses because of reduced milk yield and may promote the development of secondary diseases. Thus, an early detection seems desirable as it enables the farmer to initiate countermeasures. To support early detection, we examine different types of data recordings and use them to build a flexible algorithm that predicts the occurence of subclinical ketosis. This approach shows promising results and can be seen as a step toward automatic health monitoring in farm animals. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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14 pages, 2754 KiB

Open AccessArticle

Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters

by Martin Elenkov, Paul Ecker, Benjamin Lukitsch, Christoph Janeczek, Michael Harasek and Margit Gföhler

Sensors 2020, 20(5), 1451; https://doi.org/10.3390/s20051451 - 6 Mar 2020

Cited by 4 | Viewed by 3544

Abstract

Blood pumps have found applications in heart support devices, oxygenators, and dialysis systems, among others. Often, there is no room for sensors, or the sensors are simply unreliable when long-term operation is required. However, control systems rely on those hard-to-measure parameters, such as [...] Read more.

Blood pumps have found applications in heart support devices, oxygenators, and dialysis systems, among others. Often, there is no room for sensors, or the sensors are simply unreliable when long-term operation is required. However, control systems rely on those hard-to-measure parameters, such as blood flow rate and pressure difference, thus their estimation takes a central role in the development process of such medical devices. The viscosity of the blood not only influences the estimation of those parameters but is often a parameter that is of great interest to both doctors and engineers. In this work, estimation methods for blood flow rate, pressure difference, and viscosity are presented using Gaussian process regression models. Different water–glycerol mixtures were used to model blood. Data was collected from a custom-built blood pump, designed for intracorporeal oxygenators in an in vitro test circuit. The estimation was performed from motor current and motor speed measurements and its accuracy was measured for: blood flow rate r² = 0.98, root mean squared error (RMSE) = 46 mL^.min⁻¹; pressure difference r² = 0.98, RMSE = 8.7 mmHg; and viscosity r² = 0.98, RMSE = 0.049 mPa^.s. The results suggest that the presented methods can be used to accurately predict blood flow rate, pressure, and viscosity online. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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10 pages, 2583 KiB

Open AccessArticle

Design and Calibration of an Instrumented Seat Post to Measure Sitting Loads While Cycling

by Dieltiens Sien, D’hondt Jordi, Marc Juwet, Keivan Shariatmadar and Mark Versteyhe

Sensors 2020, 20(5), 1384; https://doi.org/10.3390/s20051384 - 3 Mar 2020

Cited by 5 | Viewed by 4346

Abstract

Traditional instrumented seat posts determine context-induced seat loads to analyze damping properties. This paper presents an enhanced instrumented seat post able to measure all six load components to resolve user-induced seat loads. User-induced cycling loads consist of all loads the user applies to [...] Read more.

Traditional instrumented seat posts determine context-induced seat loads to analyze damping properties. This paper presents an enhanced instrumented seat post able to measure all six load components to resolve user-induced seat loads. User-induced cycling loads consist of all loads the user applies to the bicycle during cycling and is measured at the steer stem, the seat post, and the pedals. Seat loads are essentially uncharted territory, as most studies only address pedal loading to study cycling technique. In this paper, a conventional seat post is redesigned by equipping it with a u-shaped component and strain gauges. The instrumented seat post is straightforward thanks to (i) the simple design, (ii) the gravitational calibration method, and (iii) the permitted clearance on the strain gauge alignment. Analyzing mean seat loading in function of the pedal cycle can provide extra insights into cycling technique and the related injuries. It is an interesting addition to the universally adopted method of utilizing singular pedal loads. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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10 pages, 495 KiB

Open AccessArticle

A Comparison of the Conventional PiG Marker Method Versus a Cluster-Based Model when recording Gait Kinematics in Trans-Tibial Prosthesis Users and the Implications for Future IMU Gait Analysis

by Manunchaya Samala, Philip Rowe, Jutima Rattanakoch and Gary Guerra

Sensors 2020, 20(5), 1255; https://doi.org/10.3390/s20051255 - 25 Feb 2020

Cited by 3 | Viewed by 4242

Abstract

Validation testing is a necessary step for inertial measurement unit (IMU) motion analysis for research and clinical use. Optical tracking systems utilize marker models which must be precise in measurement and mitigate skin artifacts. Prosthesis wearers present challenges to optical tracking marker model [...] Read more.

Validation testing is a necessary step for inertial measurement unit (IMU) motion analysis for research and clinical use. Optical tracking systems utilize marker models which must be precise in measurement and mitigate skin artifacts. Prosthesis wearers present challenges to optical tracking marker model choice. Seven participants were recruited and underwent simultaneous motion capture from two marker sets; Plug in Gait (PiG) and the Strathclyde Cluster Model (SCM). Variability of joint kinematics within and between subjects was evaluated. Variability was higher for PiG than SCM for all parameters. The within-subjects variability as reported by the average standard deviation (SD), was below 5.6° for all rotations of the hip on the prosthesis side for all participants for both methods, with an average of 2.1° for PiG and 2.5° for SCM. Statistically significant differences in joint parameters caused by a change in the protocol were evident in the sagittal plane (p < 0.05) on the amputated side. Trans-tibial gait analysis was best achieved by use of the SCM. The SCM protocol appeared to provide kinematic measurements with a smaller variability than that of the PiG. Validation studies for prosthesis wearer populations must reconsider the marker protocol for gold standard comparisons with IMUs. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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20 pages, 11054 KiB

Open AccessArticle

A Novel Sensorised Insole for Sensing Feet Pressure Distributions

by Ines Sorrentino, Francisco Javier Andrade Chavez, Claudia Latella, Luca Fiorio, Silvio Traversaro, Lorenzo Rapetti, Yeshasvi Tirupachuri, Nuno Guedelha, Marco Maggiali, Simeone Dussoni, Giorgio Metta and Daniele Pucci

Sensors 2020, 20(3), 747; https://doi.org/10.3390/s20030747 - 29 Jan 2020

Cited by 27 | Viewed by 8296

Abstract

Wearable sensors are gaining in popularity because they enable outdoor experimental monitoring. This paper presents a cost-effective sensorised insole based on a mesh of tactile capacitive sensors. Each sensor’s spatial resolution is about 4 taxels/cm

^{2}

in order to have an accurate reconstruction [...] Read more.

Wearable sensors are gaining in popularity because they enable outdoor experimental monitoring. This paper presents a cost-effective sensorised insole based on a mesh of tactile capacitive sensors. Each sensor’s spatial resolution is about 4 taxels/cm

^{2}

in order to have an accurate reconstruction of the contact pressure distribution. As a consequence, the insole provides information such as contact forces, moments, and centre of pressure. To retrieve this information, a calibration technique that fuses measurements from a vacuum chamber and shoes equipped with force/torque sensors is proposed. The validation analysis shows that the best performance achieved a root mean square error (RMSE) of about

7 N

for the contact forces and

2 N m

for the contact moments when using the force/torque shoe data as ground truth. Thus, the insole may be an alternative to force/torque sensors for certain applications, with a considerably more cost-effective and less invasive hardware. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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20 pages, 5162 KiB

Open AccessArticle

An Exploration of Machine-Learning Estimation of Ground Reaction Force from Wearable Sensor Data

by Danica Hendry, Ryan Leadbetter, Kristoffer McKee, Luke Hopper, Catherine Wild, Peter O’Sullivan, Leon Straker and Amity Campbell

Sensors 2020, 20(3), 740; https://doi.org/10.3390/s20030740 - 29 Jan 2020

Cited by 19 | Viewed by 5090

Abstract

This study aimed to develop a wearable sensor system, using machine-learning models, capable of accurately estimating peak ground reaction force (GRF) during ballet jumps in the field. Female dancers (n = 30) performed a series of bilateral and unilateral ballet jumps. Dancers wore [...] Read more.

This study aimed to develop a wearable sensor system, using machine-learning models, capable of accurately estimating peak ground reaction force (GRF) during ballet jumps in the field. Female dancers (n = 30) performed a series of bilateral and unilateral ballet jumps. Dancers wore six ActiGraph Link wearable sensors (100 Hz). Data were collected simultaneously from two AMTI force platforms and synchronised with the ActiGraph data. Due to sensor hardware malfunctions and synchronisation issues, a multistage approach to model development, using a reduced data set, was taken. Using data from the 14 dancers with complete multi-sensor synchronised data, the best single sensor was determined. Subsequently, the best single sensor model was refined and validated using all available data for that sensor (23 dancers). Root mean square error (RMSE) in body weight (BW) and correlation coefficients (r) were used to assess the GRF profile, and Bland–Altman plots were used to assess model peak GRF accuracy. The model based on sacrum data was the most accurate single sensor model (unilateral landings: RMSE = 0.24 BW, r = 0.95; bilateral landings: RMSE = 0.21 BW, r = 0.98) with the refined model still showing good accuracy (unilateral: RMSE = 0.42 BW, r = 0.80; bilateral: RMSE = 0.39 BW, r = 0.92). Machine-learning models applied to wearable sensor data can provide a field-based system for GRF estimation during ballet jumps. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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10 pages, 1677 KiB

Open AccessArticle

Validity and Reliability of an Inertial Device for Measuring Dynamic Weight-Bearing Ankle Dorsiflexion

by José M. Oliva-Lozano, Isabel Martín-Fuentes and José M. Muyor

Sensors 2020, 20(2), 399; https://doi.org/10.3390/s20020399 - 10 Jan 2020

Cited by 9 | Viewed by 5196

Abstract

A decrease in ankle dorsiflexion causes changes in biomechanics, and different instruments have been used for ankle dorsiflexion testing under static conditions. Consequently, the industry of inertial sensors has developed easy-to-use devices, which measure dynamic ankle dorsiflexion and provide additional parameters such as [...] Read more.

A decrease in ankle dorsiflexion causes changes in biomechanics, and different instruments have been used for ankle dorsiflexion testing under static conditions. Consequently, the industry of inertial sensors has developed easy-to-use devices, which measure dynamic ankle dorsiflexion and provide additional parameters such as velocity, acceleration, or movement deviation. Therefore, the aims of this study were to analyze the concurrent validity and test-retest reliability of an inertial device for measuring dynamic weight-bearing ankle dorsiflexion. Sixteen participants were tested using an inertial device (WIMU) and a digital inclinometer. Ankle dorsiflexion from left and right ankle repetitions was used for validity analysis, whereas test-retest reliability was analyzed by comparing measurements from the first and second days. The standard error of the measurement (SEM) between the instruments was very low for both ankle measurements (SEM < 0.6°). No significant differences between instruments were found for the left ankle measurement (p > 0.05) even though a significant systematic bias (~1.77°) was found for the right ankle (d = 0.79). R² was very close to 1 in the left and right ankles (R² = 0.85–0.89) as well as the intraclass correlation coefficient (ICC > 0.95). Test-retest reliability analysis showed that systematic bias was below 1° for both instruments, even though a systematic bias (~1.50°) with small effect size was found in the right ankle (d = 0.49) with WIMU. The ICC was very close to 1 and the coefficient of variation (CV) was lower than 4% in both instruments. Thus, WIMU is a valid and reliable inertial device for measuring dynamic weight-bearing ankle dorsiflexion. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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29 pages, 20346 KiB

Open AccessArticle

Six-Axis Force Torque Sensor Model-Based In Situ Calibration Method and Its Impact in Floating-Based Robot Dynamic Performance

by Francisco Javier Andrade Chavez, Silvio Traversaro and Daniele Pucci

Sensors 2019, 19(24), 5521; https://doi.org/10.3390/s19245521 - 13 Dec 2019

Cited by 8 | Viewed by 7303

Abstract

A crucial part of dynamic motions is the interaction with other objects or the environment. Floating base robots have yet to perform these motions repeatably and reliably. Force torque sensors are able to provide the full description of a contact. Despite that, their [...] Read more.

A crucial part of dynamic motions is the interaction with other objects or the environment. Floating base robots have yet to perform these motions repeatably and reliably. Force torque sensors are able to provide the full description of a contact. Despite that, their use beyond a simple threshold logic is not widespread in floating base robots. Force torque sensors might change performance when mounted, which is why in situ calibration methods can improve the performance of robots by ensuring better force torque measurements. The Model-Based in situ calibration method with temperature compensation has shown promising results in improving FT sensor measurements. There are two main goals for this paper. The first is to facilitate the use and understanding of the method by providing guidelines that show their usefulness through experimental results. Then the impact of having better FT measurements with no temperature drift are demonstrated by proving that the offset estimated with this method is still useful days and even a month from the time of estimation. The effect of this is showcased by comparing the sensor response with different offsets simultaneously during real robot experiments. Furthermore, quantitative results of the improvement in dynamic behaviors due to the in situ calibration are shown. Finally, we show how using better FT measurements as feedback in low and high level controllers can impact the performance of floating base robots during dynamic motions. Experiments were performed on the floating base robot iCub. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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24 pages, 7065 KiB

Open AccessArticle

Development of a Data Logger for Capturing Human-Machine Interaction in Wheelchair Head-Foot Steering Sensor System in Dyskinetic Cerebral Palsy

by Sotirios Gakopoulos, Ioana Gabriela Nica, Saranda Bekteshi, Jean-Marie Aerts, Elegast Monbaliu and Hans Hallez

Sensors 2019, 19(24), 5404; https://doi.org/10.3390/s19245404 - 7 Dec 2019

Cited by 7 | Viewed by 5729

Abstract

The use of data logging systems for capturing wheelchair and user behavior has increased rapidly over the past few years. Wheelchairs ensure more independent mobility and better quality of life for people with motor disabilities. Especially, for people with complex movement disorders, such [...] Read more.

The use of data logging systems for capturing wheelchair and user behavior has increased rapidly over the past few years. Wheelchairs ensure more independent mobility and better quality of life for people with motor disabilities. Especially, for people with complex movement disorders, such as dyskinetic cerebral palsy (DCP) who lack the ability to walk or to handle objects, wheelchairs offer a means of integration into daily life. The mobility of DCP patients is based on a head-foot wheelchair steering system. In this work, a data logging system is proposed to capture data from human-wheelchair interaction for the head-foot steering system. Additionally, the data logger provides an interface to multiple Inertial Measurement Units (IMUs) placed on the body of the wheelchair user. The system provides accurate and real-time information from head-foot navigation system pressure sensors on the wheelchair during driving. This system was used as a tool to obtain further insights into wheelchair control and steering behavior of people diagnosed with DCP in comparison with a healthy subject. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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14 pages, 4106 KiB

Open AccessArticle

Cross-Country Skiing Analysis and Ski Technique Detection by High-Precision Kinematic Global Navigation Satellite System

by Masaki Takeda, Naoto Miyamoto, Takaaki Endo, Olli Ohtonen, Stefan Lindinger, Vesa Linnamo and Thomas Stöggl

Sensors 2019, 19(22), 4947; https://doi.org/10.3390/s19224947 - 13 Nov 2019

Cited by 13 | Viewed by 4188

Abstract

Cross-country skiing (XCS) embraces a broad variety of techniques applied like a gear system according to external conditions, slope topography, and skier-related factors. The continuous detection of applied skiing techniques and cycle characteristics by application of unobtrusive sensor technology can provide useful information [...] Read more.

Cross-country skiing (XCS) embraces a broad variety of techniques applied like a gear system according to external conditions, slope topography, and skier-related factors. The continuous detection of applied skiing techniques and cycle characteristics by application of unobtrusive sensor technology can provide useful information to enhance the quality of training and competition. (1) Background: We evaluated the possibility of using a high-precision kinematic global navigation satellite system (GNSS) to detect cross-country skiing classical style technique. (2) Methods: A world-class male XC skier was analyzed during a classical style 5.3-km time trial recorded with a high-precision kinematic GNSS attached to the skier’s head. A video camera was mounted on the lumbar region of the skier to detect the type and number of cycles of each technique used during the entire time trial. Based on the GNSS trajectory, distinct patterns of head displacement (up-down head motion) for each classical technique (e.g., diagonal stride (DIA), double poling (DP), kick double poling (KDP), herringbone (HB), and downhill) were defined. The applied skiing technique, skiing duration, skiing distance, skiing speed, and cycle time within a technique and the number of cycles were visually analyzed using both the GNSS signal and the video data by independent persons. Distinct patterns for each technique were counted by two methods: Head displacement with course inclination and without course inclination (net up-down head motion). (3) Results: Within the time trial, 49.6% (6 min, 46 s) was DP, 18.7% (2 min, 33 s) DIA, 6.1% (50 s) KDP, 3.3% (27 s) HB, and 22.3% (3 min, 03 s) downhill with respect to total skiing time (13 min, 09 s). The %Match for both methods 1 and 2 (net head motion) was high: 99.2% and 102.4%, respectively, for DP; 101.7% and 95.9%, respectively, for DIA; 89.4% and 100.0%, respectively, for KDP; 86.0% and 96.5%, respectively, in HB; and 98.6% and 99.6%, respectively, in total. (4) Conclusions: Based on the results of our study, it is suggested that a high-precision kinematic GNSS can be applied for precise detection of the type of technique, and the number of cycles used, duration, skiing speed, skiing distance, and cycle time for each technique, during a classical style XCS race. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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17 pages, 6313 KiB

Open AccessArticle

A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation

by Taha Khan, Lina E. Lundgren, Eric Järpe, M. Charlotte Olsson and Pelle Viberg

Sensors 2019, 19(21), 4729; https://doi.org/10.3390/s19214729 - 31 Oct 2019

Cited by 20 | Viewed by 5440

Abstract

Blood lactate accumulation is a crucial fatigue indicator during sports training. Previous studies have predicted cycling fatigue using surface-electromyography (sEMG) to non-invasively estimate lactate concentration in blood. This study used sEMG to predict muscle fatigue while running and proposes a novel method for [...] Read more.

Blood lactate accumulation is a crucial fatigue indicator during sports training. Previous studies have predicted cycling fatigue using surface-electromyography (sEMG) to non-invasively estimate lactate concentration in blood. This study used sEMG to predict muscle fatigue while running and proposes a novel method for the automatic classification of running fatigue based on sEMG. Data were acquired from 12 runners during an incremental treadmill running-test using sEMG sensors placed on the vastus-lateralis, vastus-medialis, biceps-femoris, semitendinosus, and gastrocnemius muscles of the right and left legs. Blood lactate samples of each runner were collected every two minutes during the test. A change-point segmentation algorithm labeled each sample with a class of fatigue level as (1) aerobic, (2) anaerobic, or (3) recovery. Three separate random forest models were trained to classify fatigue using 36 frequency, 51 time-domain, and 36 time-event sEMG features. The models were optimized using a forward sequential feature elimination algorithm. Results showed that the random forest trained using distributive power frequency of the sEMG signal of the vastus-lateralis muscle alone could classify fatigue with high accuracy. Importantly for this feature, group-mean ranks were significantly different (p < 0.01) between fatigue classes. Findings support using this model for monitoring fatigue levels during running. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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9 pages, 1473 KiB

Open AccessArticle

Tongue Rehabilitation Device for Dysphagic Patients

by Mario Milazzo, Andrea Panepinto, Angelo Maria Sabatini and Serena Danti

Sensors 2019, 19(21), 4657; https://doi.org/10.3390/s19214657 - 26 Oct 2019

Cited by 9 | Viewed by 5185

Abstract

Dysphagia refers to difficulty in swallowing often associated with syndromic disorders. In dysphagic patients’ rehabilitation, tongue motility is usually treated and monitored via simple exercises, in which the tongue is pushed against a depressor held by the speech therapist in different directions. In [...] Read more.

Dysphagia refers to difficulty in swallowing often associated with syndromic disorders. In dysphagic patients’ rehabilitation, tongue motility is usually treated and monitored via simple exercises, in which the tongue is pushed against a depressor held by the speech therapist in different directions. In this study, we developed and tested a simple pressure/force sensor device, named “Tonic Tongue (ToTo)”, intended to support training and monitoring tasks for the rehabilitation of tongue musculature. It consists of a metallic frame holding a ball bearing support equipped with a sterile disposable depressor, whose angular displacements are counterbalanced by extensional springs. The conversion from angular displacement to force is managed using a simple mechanical model of ToTo operation. Since the force exerted by the tongue in various directions can be estimated, quantitative assessment of the outcome of a given training program is possible. A first prototype of ToTo was tested on 26 healthy adults, who were trained for one month. After the treatment, we observed a statistically significant improvement with a force up to 2.2 N (median value) in all tested directions of pushing, except in the downward direction, in which the improvement was slightly higher than 5 N (median value). ToTo promises to be an innovative and reliable device that can be used for the rehabilitation of dysphagic patients. Moreover, since it is a self-standing device, it could be used as a point-of-care solution for in-home rehabilitation management of dysphasia. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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19 pages, 603 KiB

Open AccessArticle

A Systematic Methodology to Analyze the Impact of Hand-Rim Wheelchair Propulsion on the Upper Limb

by Blanca Larraga-García, Vicente Lozano-Berrio, Álvaro Gutiérrez, Ángel Gil-Agudo and Antonio J. del-Ama

Sensors 2019, 19(21), 4643; https://doi.org/10.3390/s19214643 - 25 Oct 2019

Cited by 7 | Viewed by 3799

Abstract

Manual wheelchair propulsion results in physical demand of the upper limb extremities that, because of its repetitive nature, can lead to chronic pathologies on spinal cord injury patients. The aim of this study was to design and test a methodology to compare kinematic [...] Read more.

Manual wheelchair propulsion results in physical demand of the upper limb extremities that, because of its repetitive nature, can lead to chronic pathologies on spinal cord injury patients. The aim of this study was to design and test a methodology to compare kinematic and kinetic variables of the upper limb joints when propelling different wheelchairs. Moreover, this methodology was used to analyze the differences that may exist between paraplegic and tetraplegic patients when propelling two different wheelchairs. Five adults with paraplegia and five adults with tetraplegia performed several propulsion tests. Participants propelled two different wheelchairs for three minutes at 0.833 m/s (3 km/h) with one minute break between the tests. Kinematic and kinetic variables of the upper limb as well as variables with respect to the propulsion style were recorded. Important differences in the kinetic and kinematic variables of the joints of the upper limb were found when comparing paraplegic and tetraplegic patients. Nevertheless, this difference depends on the wheelchair used. As expected, in all tests, the shoulder shows to be the most impacted joint. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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20 pages, 7276 KiB

Open AccessArticle

Smartphone-Based 3D Indoor Pedestrian Positioning through Multi-Modal Data Fusion

by Hongyu Zhao, Wanli Cheng, Ning Yang, Sen Qiu, Zhelong Wang and Jianjun Wang

Sensors 2019, 19(20), 4554; https://doi.org/10.3390/s19204554 - 19 Oct 2019

Cited by 37 | Viewed by 4972

Abstract

Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone’s built-in inertial sensors [...] Read more.

Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone’s built-in inertial sensors have attracted much attention in such environments. However, smartphone-based PDR systems are facing various challenges, especially the heading drift, which leads to the phenomenon of estimated walking path passing through walls. In this paper, the 2D PDR system is implemented by using a pocket-worn smartphone, and then enhanced by introducing a map-matching algorithm that employs a particle filter to prevent the wall-crossing problem. In addition, to extend the PDR system for 3D applications, the smartphone’s built-in barometer is used to measure the pressure variation associated to the pedestrian’s vertical displacement. Experimental results show that the map-matching algorithm based on a particle filter can effectively solve the wall-crossing problem and improve the accuracy of indoor PDR. By fusing the barometer readings, the vertical displacement can be calculated to derive the floor transition information. Despite the inherent sensor noises and complex pedestrian movements, smartphone-based 3D pedestrian positioning systems have considerable potential for indoor location-based services (LBS). Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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30 pages, 7456 KiB

Open AccessArticle

On the Noise Complexity in an Optical Motion Capture Facility

by Przemysław Skurowski and Magdalena Pawlyta

Sensors 2019, 19(20), 4435; https://doi.org/10.3390/s19204435 - 13 Oct 2019

Cited by 9 | Viewed by 4023

Abstract

Optical motion capture systems are state-of-the-art in motion acquisition; however, like any measurement system they are not error-free: noise is their intrinsic feature. The works so far mostly employ a simple noise model, expressing the uncertainty as a simple variance. In the work, [...] Read more.

Optical motion capture systems are state-of-the-art in motion acquisition; however, like any measurement system they are not error-free: noise is their intrinsic feature. The works so far mostly employ a simple noise model, expressing the uncertainty as a simple variance. In the work, we demonstrate that it might be not sufficient and we prove the existence of several types of noise and demonstrate how to quantify them using Allan variance. Such a knowledge is especially important for using optical motion capture to calibrate other techniques, and for applications requiring very fine quality of recording. For the automated readout of the noise coefficients, we solve the multidimensional regression problem using sophisticated metaheuristics in the exploration-exploitation scheme. We identified in the laboratory the notable contribution to the overall noise from white noise and random walk, and a minor contribution from blue noise and flicker, whereas the violet noise is absent. Besides classic types of noise we identified the presence of the correlated noises and periodic distortion. We analyzed also how the noise types scale with an increasing number of cameras. We had also the opportunity to observe the influence of camera failure on the overall performance. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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20 pages, 17778 KiB

Open AccessArticle

Analysis of Agile Canine Gait Characteristics Using Accelerometry

by Hasti Hayati, Fatemeh Mahdavi and David Eager

Sensors 2019, 19(20), 4379; https://doi.org/10.3390/s19204379 - 10 Oct 2019

Cited by 12 | Viewed by 5151

Abstract

The high rate of severe injuries associated with racing greyhounds poses a significant problem for both animal welfare and the racing industry. Using accelerometry to develop a better understanding of the complex gait of these agile canines may help to eliminate injury contributing [...] Read more.

The high rate of severe injuries associated with racing greyhounds poses a significant problem for both animal welfare and the racing industry. Using accelerometry to develop a better understanding of the complex gait of these agile canines may help to eliminate injury contributing factors. This study used a single Inertial Measurement Unit (IMU) equipped with a tri-axial accelerometer to characterise the galloping of thirty-one greyhounds on five different race tracks. The dorsal-ventral and anterior-posterior accelerations were analysed in both the time and frequency domains. The fast Fourier transform (FFT) and Morlet wavelet transform were applied to signals. The time-domain signals were synced with the corresponding high frame rate videos of the race. It was observed that the acceleration peaks in the dorsal-ventral accelerations correspond to the hind-leg strikes which were noted to be fifteen times the greyhound’s weight. The FFT analysis showed that the stride frequencies in all tracks were around 3.5 Hz. The Morlet wavelet analysis also showed a reduction in both the frequency and magnitude of signals, which suggests a speed reduction throughout the race. Also, by detecting abrupt changes along the track, the wavelet analysis highlighted potentially hazardous locations on the track. In conclusion, the methods applied in this research contribute to animal safety and welfare by eliminating the factors leading to injuries through optimising the track design and surface type. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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11 pages, 3805 KiB

Open AccessArticle

Development of a New Embedded Dynamometer for the Measurement of Forces and Torques at the Ski-Binding Interface

by Frédéric Meyer, Alain Prenleloup and Alain Schorderet

Sensors 2019, 19(19), 4324; https://doi.org/10.3390/s19194324 - 7 Oct 2019

Cited by 11 | Viewed by 5152

Abstract

In alpine skiing, understanding the interaction between skiers and snow is of primary importance for both injury prevention as well as performance analysis. Risk of injuries is directly linked to constraints undergone by the skier. A force platform placed as an interface between [...] Read more.

In alpine skiing, understanding the interaction between skiers and snow is of primary importance for both injury prevention as well as performance analysis. Risk of injuries is directly linked to constraints undergone by the skier. A force platform placed as an interface between the ski and the skier should allow a better understanding of these constraints to be obtained to thereby develop a more reliable release system of binding. It should also provide useful information to allow for better physical condition training of athletes and non-professional skiers to reduce the risk of injury. Force and torque measurements also allow for a better understanding of the skiers’ technique (i.e., load evolution during turns, force distribution between left and right leg…). Therefore, the aim of this project was to develop a new embedded force platform that could be placed between the ski boot and the binding. First, the physical specifications of the dynamometer are listed as well as the measurement scope. Then, several iterations were performed on parametric 3D modeling and finite element analysis to obtain an optimal design. Two platforms were then machined and equipped with strain gauges. Finally, the calibration was performed on a dedicated test bench. The accuracy of the system was between 1.3 and 12.8% of the applied load. These results show a very good linearity of the system, which indicate a great outcome of the design. Field tests also highlighted the ease of use and reliability. This new dynamometer will allow skiers to wear their own equipment while measuring force and torque in real skiing conditions. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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13 pages, 3646 KiB

Open AccessArticle

Testing of a MEMS Dynamic Inclinometer Using the Stewart Platform

by Zhihua Liu, Chenguang Cai, Ming Yang and Ying Zhang

Sensors 2019, 19(19), 4233; https://doi.org/10.3390/s19194233 - 29 Sep 2019

Cited by 23 | Viewed by 5093

Abstract

The micro-electro-mechanical system (MEMS) dynamic inclinometer integrates a tri-axis gyroscope and a tri-axis accelerometer for real-time tilt measurement. The Stewart platform has the ability to generate six degrees of freedom of spatial orbits. The method of applying spatial orbits to the testing of [...] Read more.

The micro-electro-mechanical system (MEMS) dynamic inclinometer integrates a tri-axis gyroscope and a tri-axis accelerometer for real-time tilt measurement. The Stewart platform has the ability to generate six degrees of freedom of spatial orbits. The method of applying spatial orbits to the testing of MEMS inclinometers is investigated. Inverse and forward kinematics are analyzed for controlling and measuring the position and orientation of the Stewart platform. The Stewart platform is controlled to generate a conical motion, based on which the sensitivities of the gyroscope, accelerometer, and tilt sensing are determined. Spatial positional orbits are also generated in order to obtain the tilt angles caused by the cross-coupling influence. The experiment is conducted to show that the tested amplitude frequency deviations of the gyroscope and tilt sensing sensitivities between the Stewart platform and the traditional rotator are less than 0.2 dB and 0.1 dB, respectively. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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11 pages, 2545 KiB

Open AccessArticle

Evaluation of Aerosol Electrospray Analysis of Metal-on-Metal Wear Particles from Simulated Total Joint Replacement

by Gobert von Skrbensky, Karoline Mühlbacher, Emir Benca, Alexander Kolb, Reinhard Windhager, Georg Reischl and Georg Reinisch

Sensors 2019, 19(17), 3751; https://doi.org/10.3390/s19173751 - 30 Aug 2019

Cited by 2 | Viewed by 2968

Abstract

Wear is a common cause for aseptic loosening in artificial joints. The purpose of this study was to develop an automated diagnostical method for identification of the number and size distribution of wear debris. For this purpose, metal debris samples were extracted from [...] Read more.

Wear is a common cause for aseptic loosening in artificial joints. The purpose of this study was to develop an automated diagnostical method for identification of the number and size distribution of wear debris. For this purpose, metal debris samples were extracted from a hip simulator and then analyzed by the electrospray method combined with a differential mobility analyzer, allowing particle detection ranging from several nanometers up to 1 µm. Wear particles were identified with a characteristic peak at 15 nm. The electrospray setup was successfully used and validated for the first time to characterize wear debris from simulated total joint replacement. The advantages of this diagnostic method are its time- and financial efficiency and its suitability for testing of different materials. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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24 pages, 1975 KiB

Open AccessArticle

Kelvin–Voigt Parameters Reconstruction of Cervical Tissue-Mimicking Phantoms Using Torsional Wave Elastography

by Antonio Callejas, Antonio Gomez, Inas H. Faris, Juan Melchor and Guillermo Rus

Sensors 2019, 19(15), 3281; https://doi.org/10.3390/s19153281 - 25 Jul 2019

Cited by 17 | Viewed by 3874

Abstract

The reconstruction of viscous properties of soft tissues, and more specifically, of cervical tissue is a challenging problem. In this paper, a new method is proposed to reconstruct the viscoelastic parameters of cervical tissue-mimicking phantoms by a Torsional Wave Elastography (TWE) technique. The [...] Read more.

The reconstruction of viscous properties of soft tissues, and more specifically, of cervical tissue is a challenging problem. In this paper, a new method is proposed to reconstruct the viscoelastic parameters of cervical tissue-mimicking phantoms by a Torsional Wave Elastography (TWE) technique. The reconstruction method, based on a Probabilistic Inverse Problem (PIP) approach, is presented and experimentally validated against Shear Wave Elastography (SWE). The anatomy of the cervical tissue has been mimicked by means of a two-layer gelatine phantom that simulates the epithelial and connective layers. Five ad hoc oil-in-gelatine phantoms were fabricated at different proportion to test the new reconstruction technique. The PIP approach was used for reconstructing the Kelvin-Voigt (KV) viscoelastic parameters by comparing the measurements obtained from the TWE technique with the synthetic signals from a Finite Difference Time Domain (FDTD) KV wave propagation model. Additionally, SWE tests were realized in order to characterize the viscoelastic properties of each batch of gelatine. Finally, validation was carried out by comparing the KV parameters inferred from the PIP with those reconstructed from the shear wave dispersion curve obtained from the SWE measurements. In order to test the degree of agreement between both techniques, a Student’s T-test and a Pearson’s correlation study were performed. The results indicate that the proposed method is able to reconstruct the KV viscoelastic properties of the cervical tissue, for both the epithelial and connective layers, as well as the thickness of the first layer with acceptable accuracy. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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20 pages, 28402 KiB

Open AccessArticle

Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques

by Claudia Latella, Silvio Traversaro, Diego Ferigo, Yeshasvi Tirupachuri, Lorenzo Rapetti, Francisco Javier Andrade Chavez, Francesco Nori and Daniele Pucci

Sensors 2019, 19(12), 2794; https://doi.org/10.3390/s19122794 - 21 Jun 2019

Cited by 14 | Viewed by 5040

Abstract

The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimation [...] Read more.

The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimation problem. The presented approach is validated by presenting experimental results of a health subject equipped with a wearable motion tracking system and a pair of shoes sensorized with force/torque sensors while performing different motion tasks, e.g., walking on a treadmill. The results show that joint torque estimates obtained by using floating-base and fixed-base approaches match satisfactorily, thus validating the present approach. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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20 pages, 15487 KiB

Open AccessArticle

Constraint-Based Optimized Human Skeleton Extraction from Single-Depth Camera

by Ruotong Li, Weixin Si, Michael Weinmann and Reinhard Klein

Sensors 2019, 19(11), 2604; https://doi.org/10.3390/s19112604 - 7 Jun 2019

Cited by 16 | Viewed by 5801

Abstract

As a cutting-edge research topic in computer vision and graphics for decades, human skeleton extraction from single-depth camera remains challenging due to possibly occurring occlusions of different body parts, huge appearance variations, and sensor noise. In this paper, we propose to incorporate human [...] Read more.

As a cutting-edge research topic in computer vision and graphics for decades, human skeleton extraction from single-depth camera remains challenging due to possibly occurring occlusions of different body parts, huge appearance variations, and sensor noise. In this paper, we propose to incorporate human skeleton length conservation and symmetry priors as well as temporal constraints to enhance the consistency and continuity for the estimated skeleton of a moving human body. Given an initial estimation of the skeleton joint positions provided per frame by the Kinect SDK or Nuitrack SDK, which do not follow the aforementioned priors and can prone to errors, our framework improves the accuracy of these pose estimates based on the length and symmetry constraints. In addition, our method is device-independent and can be integrated into skeleton extraction SDKs for refinement, allowing the detection of outliers within the initial joint location estimates and predicting new joint location estimates following the temporal observations. The experimental results demonstrate the effectiveness and robustness of our approach in several cases. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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Review

Jump to: Research

16 pages, 4613 KiB

Open AccessReview

Ultrasound as a Tool to Study Muscle–Tendon Functions during Locomotion: A Systematic Review of Applications

by Christoph Leitner, Pascal A. Hager, Harald Penasso, Markus Tilp, Luca Benini, Christian Peham and Christian Baumgartner

Sensors 2019, 19(19), 4316; https://doi.org/10.3390/s19194316 - 5 Oct 2019

Cited by 21 | Viewed by 6176

Abstract

Movement science investigating muscle and tendon functions during locomotion utilizes commercial ultrasound imagers built for medical applications. These limit biomechanics research due to their form factor, range of view, and spatio-temporal resolution. This review systematically investigates the technical aspects of applying ultrasound as [...] Read more.

Movement science investigating muscle and tendon functions during locomotion utilizes commercial ultrasound imagers built for medical applications. These limit biomechanics research due to their form factor, range of view, and spatio-temporal resolution. This review systematically investigates the technical aspects of applying ultrasound as a research tool to investigate human and animal locomotion. It provides an overview on the ultrasound systems used and of their operating parameters. We present measured fascicle velocities and discuss the results with respect to operating frame rates during recording. Furthermore, we derive why muscle and tendon functions should be recorded with a frame rate of at least 150 Hz and a range of view of 250 mm. Moreover, we analyze why and how the development of better ultrasound observation devices at the hierarchical level of muscles and tendons can support biomechanics research. Additionally, we present recent technological advances and their possible application. We provide a list of recommendations for the development of a more advanced ultrasound sensor system class targeting biomechanical applications. Looking to the future, mobile, ultrafast ultrasound hardware technologies create immense opportunities to expand the existing knowledge of human and animal movement. Full article

(This article belongs to the Special Issue Sensors for Biomechanics Application)

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