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16 pages, 16859 KiB

Open AccessArticle

Comparing Loose Clothing-Mounted Sensors with Body-Mounted Sensors in the Analysis of Walking

by Udeni Jayasinghe, Faustina Hwang and William S. Harwin

Sensors 2022, 22(17), 6605; https://doi.org/10.3390/s22176605 - 1 Sep 2022

Cited by 11 | Viewed by 2361

Abstract

A person’s walking pattern can reveal important information about their health. Mounting multiple sensors onto loose clothing potentially offers a comfortable way of collecting data about walking and other human movement. This research investigates how well the data from three sensors mounted on [...] Read more.

A person’s walking pattern can reveal important information about their health. Mounting multiple sensors onto loose clothing potentially offers a comfortable way of collecting data about walking and other human movement. This research investigates how well the data from three sensors mounted on the lateral side of clothing (on a pair of trousers near the waist, upper thigh and lower shank) correlate with the data from sensors mounted on the frontal side of the body. Data collected from three participants (two male, one female) for two days were analysed. Gait cycles were extracted based on features in the lower-shank accelerometry and analysed in terms of sensor-to-vertical angles (SVA). The correlations in SVA between the clothing- and body-mounted sensor pairs were analysed. Correlation coefficients above 0.76 were found for the waist sensor pairs, while the thigh and lower-shank sensor pairs had correlations above 0.90. The cyclical nature of gait cycles was evident in the clothing data, and it was possible to distinguish the stance and swing phases of walking based on features in the clothing data. Furthermore, simultaneously recording data from the waist, thigh, and shank was helpful in capturing the movement of the whole leg. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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10 pages, 1738 KiB

Open AccessArticle

Season Match Loads of a Portuguese Under-23 Soccer Team: Differences between Different Starting Statuses throughout the Season and Specific Periods within the Season Using Global Positioning Systems

by João Barreira, Fábio Y. Nakamura, Ricardo Ferreira, João Pereira, Rodrigo Aquino and Pedro Figueiredo

Sensors 2022, 22(17), 6379; https://doi.org/10.3390/s22176379 - 24 Aug 2022

Cited by 4 | Viewed by 2029

Abstract

This study aimed to quantify the external match loads (EMLs) of a Portuguese u-23 soccer team, competing at the highest national level for the age group, comparing players with different starting status throughout a competitive season and specific blocks. Thirty-five outfield soccer players [...] Read more.

This study aimed to quantify the external match loads (EMLs) of a Portuguese u-23 soccer team, competing at the highest national level for the age group, comparing players with different starting status throughout a competitive season and specific blocks. Thirty-five outfield soccer players were split into three groups for the entire season analysis and for each 3-month block, based on the percentage of games played as a starter. The three groups consisted of “starters” (≥55% of the games as a starter), “fringe” (30–54%), and “non-starters” (<30%). EMLs were recorded using 10 Hz GPS technology throughout the whole season (26 matches). Differences (p < 0.05) were found for total distance (TD), exposure time, and the number of accelerations and decelerations between starters and non-starters throughout the season (d = 0.73 to 1.08), and within each block (d = 0.59 to 1.68). Differences were also found between starters and fringe players for the number of accelerations in Block 2 (p = 0.03; d = 0.69), and TD (p = 0.006; d = 1) and exposure time (p = 0.006; d = 0.95) in Block 3. Differences in the EML were almost always accompanied by large differences in game time. Our results highlight the differences in the EML of starters and non-starters, emphasizing the need for compensatory training, especially with players that obtain significantly less playing time, to prepare the players for match demands (e.g., high-intensity efforts such as sprinting, accelerations, and decelerations). Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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12 pages, 3974 KiB

Open AccessArticle

Symmetry Function: The Differences between Active and Non-Active Above-the-Knee Amputees

by Mateusz Kowal, Sławomir Winiarski, Ewa Gieysztor, Anna Kołcz, Ilias Dumas and Małgorzata Paprocka-Borowicz

Sensors 2022, 22(16), 5933; https://doi.org/10.3390/s22165933 - 9 Aug 2022

Cited by 1 | Viewed by 1909

Abstract

The number of patients with unilateral above-knee amputation (AKA) due to non-vascular causes has remained stable over the years, at 0.92 per 1000 people per year. Post-AKA individuals are at risk of experiencing a higher incidence of chronic pain. Post rehabilitation, it is [...] Read more.

The number of patients with unilateral above-knee amputation (AKA) due to non-vascular causes has remained stable over the years, at 0.92 per 1000 people per year. Post-AKA individuals are at risk of experiencing a higher incidence of chronic pain. Post rehabilitation, it is estimated that between 16–62% of patients with musculoskeletal disabilities fail to meet the minimum criteria for physical activity in comparison to a healthy population. The current study included 14 participants (11 men and 3 women) with a mean age of 46.1 ± 14.2 years, body height of 1.76 ± 0.09 m, and weight of 79.6 ± 18.3 kg, who were all post-unilateral above-the-knee amputees. Patients in the study were divided into two groups: active (AC) and non-active (NAC). This study was conducted in a certified Laboratory of Biomechanical Analysis using the BTS Smart-E system (BTS Bioengineering). In order to investigate the symmetry function (SF) of gait, the only measurements included were the time series assessment of gait variables defining pelvic and lower limb joint motion and ground reaction forces (GRF). Both groups had an asymmetrical gait pattern with a different magnitude and relative position in the gait cycle, which was revealed by SF. The differences in terms of median, minimum, and maximum were statistically significant (p < 0.05), with SF ranging from –25 to 24% for the AC group and from 43 to 77% (59% on average) for the NAC group. The AC’s pattern was more symmetrical compared to the NAC’s pattern, especially in the case of pelvic and hip joint motion. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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28 pages, 5117 KiB

Open AccessArticle

System Comparison for Gait and Balance Monitoring Used for the Evaluation of a Home-Based Training

by Clara Rentz, Mehran Sahandi Far, Maik Boltes, Alfons Schnitzler, Katrin Amunts, Juergen Dukart and Martina Minnerop

Sensors 2022, 22(13), 4975; https://doi.org/10.3390/s22134975 - 30 Jun 2022

Cited by 7 | Viewed by 2632

Abstract

There are currently no standard methods for evaluating gait and balance performance at home. Smartphones include acceleration sensors and may represent a promising and easily accessible tool for this purpose. We performed an interventional feasibility study and compared a smartphone-based approach with two [...] Read more.

There are currently no standard methods for evaluating gait and balance performance at home. Smartphones include acceleration sensors and may represent a promising and easily accessible tool for this purpose. We performed an interventional feasibility study and compared a smartphone-based approach with two standard gait analysis systems (force plate and motion capturing systems). Healthy adults (n = 25, 44.1 ± 18.4 years) completed two laboratory evaluations before and after a three-week gait and balance training at home. There was an excellent agreement between all systems for stride time and cadence during normal, tandem and backward gait, whereas correlations for gait velocity were lower. Balance variables of both standard systems were moderately intercorrelated across all stance tasks, but only few correlated with the corresponding smartphone measures. Significant differences over time were found for several force plate and mocap system-obtained gait variables of normal, backward and tandem gait. Changes in balance variables over time were more heterogeneous and not significant for any system. The smartphone seems to be a suitable method to measure cadence and stride time of different gait, but not balance, tasks in healthy adults. Additional optimizations in data evaluation and processing may further improve the agreement between the analysis systems. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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13 pages, 10844 KiB

Open AccessArticle

Novel Soft Haptic Biofeedback—Pilot Study on Postural Balance and Proprioception

by Mert Aydin, Rahim Mutlu, Dilpreet Singh, Emre Sariyildiz, Robyn Coman, Elizabeth Mayland, Jonathan Shemmell and Winson Lee

Sensors 2022, 22(10), 3779; https://doi.org/10.3390/s22103779 - 16 May 2022

Cited by 5 | Viewed by 3159

Abstract

Sensory feedback is critical in proprioception and balance to orchestrate muscles to perform targeted motion(s). Biofeedback plays a significant role in substituting such sensory data when sensory functions of an individual are reduced or lost such as neurological disorders including stroke causing loss [...] Read more.

Sensory feedback is critical in proprioception and balance to orchestrate muscles to perform targeted motion(s). Biofeedback plays a significant role in substituting such sensory data when sensory functions of an individual are reduced or lost such as neurological disorders including stroke causing loss of sensory and motor functions requires compensation of both motor and sensory functions. Biofeedback substitution can be in the form of several means: mechanical, electrical, chemical and/or combination. This study proposes a soft monolithic haptic biofeedback device prototyped and pilot tests were conducted with healthy participants that balance and proprioception of the wearer were improved with applied mechanical stimuli on the lower limb(s). The soft monolithic haptic biofeedback device has been developed and manufactured using fused deposition modelling (FDM) that employs soft and flexible materials with low elastic moduli. Experimental results of the pilot tests show that the soft haptic device can effectively improve the balance of the wearer as much as can provide substitute proprioceptive feedback which are critical elements in robotic rehabilitation. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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20 pages, 3524 KiB

Open AccessArticle

Adapting Semi-Active Prostheses to Real-World Movements: Sensing and Controlling the Dynamic Mean Ankle Moment Arm with a Variable-Stiffness Foot on Ramps and Stairs

by Jennifer K. Leestma, Katherine Heidi Fehr and Peter G. Adamczyk

Sensors 2021, 21(18), 6009; https://doi.org/10.3390/s21186009 - 8 Sep 2021

Cited by 5 | Viewed by 3287

Abstract

(1) Background: Semi-active prosthetic feet can provide adaptation in different circumstances, enabling greater function with less weight and complexity than fully powered prostheses. However, determining how to control semi-active devices is still a challenge. The dynamic mean ankle moment arm (DMAMA) provides a [...] Read more.

(1) Background: Semi-active prosthetic feet can provide adaptation in different circumstances, enabling greater function with less weight and complexity than fully powered prostheses. However, determining how to control semi-active devices is still a challenge. The dynamic mean ankle moment arm (DMAMA) provides a suitable biomechanical metric, as its simplicity matches that of a semi-active device. However, it is unknown how stiffness and locomotion modes affect DMAMA, which is necessary to create closed-loop controllers for semi-active devices. In this work, we develop a method to use only a prosthesis-embedded load sensor to measure DMAMA and classify locomotion modes, with the goal of achieving mode-dependent, closed-loop control of DMAMA using a variable-stiffness prosthesis. We study how stiffness and ground incline affect the DMAMA, and we establish the feasibility of classifying locomotion modes based exclusively on the load sensor. (2) Methods: Human subjects walked on level ground, ramps, and stairs while wearing a variable-stiffness prosthesis in low-, medium-, and high-stiffness settings. We computed DMAMA from sagittal load sensor data and prosthesis geometric measurements. We used linear mixed-effects models to determine subject-independent and subject-dependent sensitivity of DMAMA to incline and stiffness. We also used a machine learning model to classify locomotion modes using only the load sensor. (3) Results: We found a positive linear sensitivity of DMAMA to stiffness on ramps and level ground. Additionally, we found a positive linear sensitivity of DMAMA to ground slope in the low- and medium-stiffness conditions and a negative interaction effect between slope and stiffness. Considerable variability suggests that applications of DMAMA as a control input should look at the running average over several strides. To examine the efficacy of real-time DMAMA-based control systems, we used a machine learning model to classify locomotion modes using only the load sensor. The classifier achieved over 95% accuracy. (4) Conclusions: Based on these findings, DMAMA has potential for use as a closed-loop control input to adapt semi-active prostheses to different locomotion modes. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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22 pages, 2031 KiB

Open AccessArticle

Performance Analysis of a Head and Eye Motion-Based Control Interface for Assistive Robots

by Sarah Stalljann, Lukas Wöhle, Jeroen Schäfer and Marion Gebhard

Sensors 2020, 20(24), 7162; https://doi.org/10.3390/s20247162 - 14 Dec 2020

Cited by 5 | Viewed by 2618

Abstract

Assistive robots support people with limited mobility in their everyday life activities and work. However, most of the assistive systems and technologies for supporting eating and drinking require a residual mobility in arms or hands. For people without residual mobility, different hands-free controls [...] Read more.

Assistive robots support people with limited mobility in their everyday life activities and work. However, most of the assistive systems and technologies for supporting eating and drinking require a residual mobility in arms or hands. For people without residual mobility, different hands-free controls have been developed. For hands-free control, the combination of different modalities can lead to great advantages and improved control. The novelty of this work is a new concept to control a robot using a combination of head and eye motions. The control unit is a mobile, compact and low-cost multimodal sensor system. A Magnetic Angular Rate Gravity (MARG)-sensor is used to detect head motion and an eye tracker enables the system to capture the user’s gaze. To analyze the performance of the two modalities, an experimental evaluation with ten able-bodied subjects and one subject with tetraplegia was performed. To assess discrete control (event-based control), a button activation task was performed. To assess two-dimensional continuous cursor control, a Fitts’s Law task was performed. The usability study was related to a use-case scenario with a collaborative robot assisting a drinking action. The results of the able-bodied subjects show no significant difference between eye motions and head motions for the activation time of the buttons and the throughput, while, using the eye tracker in the Fitts’s Law task, the error rate was significantly higher. The subject with tetraplegia showed slightly better performance for button activation when using the eye tracker. In the use-case, all subjects were able to use the control unit successfully to support the drinking action. Due to the limited head motion of the subject with tetraplegia, button activation with the eye tracker was slightly faster than with the MARG-sensor. A further study with more subjects with tetraplegia is planned, in order to verify these results. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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14 pages, 2150 KiB

Open AccessArticle

Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration

by Hanjin Jo, Woong Choi, Geonhui Lee, Wookhyun Park and Jaehyo Kim

Sensors 2020, 20(21), 6368; https://doi.org/10.3390/s20216368 - 8 Nov 2020

Cited by 3 | Viewed by 2756

Abstract

The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human–robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominant hands in tracking a target in the three-dimensional space. We compared [...] Read more.

The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human–robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominant hands in tracking a target in the three-dimensional space. We compared the circular tracking performances of the hands on the frontal plane of the virtual reality space in terms of radial position error (ΔR), phase error (Δθ), acceleration error (Δa), and dimensionless squared jerk (DSJ) at four different speeds for 30 subjects. ΔR and Δθ significantly differed at relatively high speeds (ΔR: 0.5 Hz; Δθ: 0.5, 0.75 Hz), with maximum values of ≤1% compared to the target trajectory radius. DSJ significantly differed only at low speeds (0.125, 0.25 Hz), whereas Δa significantly differed at all speeds. In summary, the feedback-control mechanism of the DH has a wider range of speed control capability and is efficient according to an energy saving model. The central nervous system (CNS) uses different models for the two hands, which react dissimilarly. Despite the precise control of the DH, both hands exhibited dependences on limb kinematic properties at high speeds (0.75 Hz). Thus, the CNS uses a different strategy according to the model for optimal results. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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25 pages, 3298 KiB

Open AccessArticle

A Wearable Sensor System for Physical Ergonomics Interventions Using Haptic Feedback

by Carl Mikael Lind, Jose Antonio Diaz-Olivares, Kaj Lindecrantz and Jörgen Eklund

Sensors 2020, 20(21), 6010; https://doi.org/10.3390/s20216010 - 23 Oct 2020

Cited by 23 | Viewed by 5337

Abstract

Work-related musculoskeletal disorders are a major concern globally affecting societies, companies, and individuals. To address this, a new sensor-based system is presented: the Smart Workwear System, aimed at facilitating preventive measures by supporting risk assessments, work design, and work technique training. The system [...] Read more.

Work-related musculoskeletal disorders are a major concern globally affecting societies, companies, and individuals. To address this, a new sensor-based system is presented: the Smart Workwear System, aimed at facilitating preventive measures by supporting risk assessments, work design, and work technique training. The system has a module-based platform that enables flexibility of sensor-type utilization, depending on the specific application. A module of the Smart Workwear System that utilizes haptic feedback for work technique training is further presented and evaluated in simulated mail sorting on sixteen novice participants for its potential to reduce adverse arm movements and postures in repetitive manual handling. Upper-arm postures were recorded, using an inertial measurement unit (IMU), perceived pain/discomfort with the Borg CR10-scale, and user experience with a semi-structured interview. This study shows that the use of haptic feedback for work technique training has the potential to significantly reduce the time in adverse upper-arm postures after short periods of training. The haptic feedback was experienced positive and usable by the participants and was effective in supporting learning of how to improve postures and movements. It is concluded that this type of sensorized system, using haptic feedback training, is promising for the future, especially when organizations are introducing newly employed staff, when teaching ergonomics to employees in physically demanding jobs, and when performing ergonomics interventions. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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21 pages, 1576 KiB

Open AccessArticle

A Virtual Reality Muscle–Computer Interface for Neurorehabilitation in Chronic Stroke: A Pilot Study

by Octavio Marin-Pardo, Christopher M. Laine, Miranda Rennie, Kaori L. Ito, James Finley and Sook-Lei Liew

Sensors 2020, 20(13), 3754; https://doi.org/10.3390/s20133754 - 4 Jul 2020

Cited by 31 | Viewed by 6124

Abstract

Severe impairment of limb movement after stroke can be challenging to address in the chronic stage of stroke (e.g., greater than 6 months post stroke). Recent evidence suggests that physical therapy can still promote meaningful recovery after this stage, but the required high [...] Read more.

Severe impairment of limb movement after stroke can be challenging to address in the chronic stage of stroke (e.g., greater than 6 months post stroke). Recent evidence suggests that physical therapy can still promote meaningful recovery after this stage, but the required high amount of therapy is difficult to deliver within the scope of standard clinical practice. Digital gaming technologies are now being combined with brain–computer interfaces to motivate engaging and frequent exercise and promote neural recovery. However, the complexity and expense of acquiring brain signals has held back widespread utilization of these rehabilitation systems. Furthermore, for people that have residual muscle activity, electromyography (EMG) might be a simpler and equally effective alternative. In this pilot study, we evaluate the feasibility and efficacy of an EMG-based variant of our REINVENT virtual reality (VR) neurofeedback rehabilitation system to increase volitional muscle activity while reducing unintended co-contractions. We recruited four participants in the chronic stage of stroke recovery, all with severely restricted active wrist movement. They completed seven 1-hour training sessions during which our head-mounted VR system reinforced activation of the wrist extensor muscles without flexor activation. Before and after training, participants underwent a battery of clinical and neuromuscular assessments. We found that training improved scores on standardized clinical assessments, equivalent to those previously reported for brain–computer interfaces. Additionally, training may have induced changes in corticospinal communication, as indexed by an increase in 12–30 Hz corticomuscular coherence and by an improved ability to maintain a constant level of wrist muscle activity. Our data support the feasibility of using muscle–computer interfaces in severe chronic stroke, as well as their potential to promote functional recovery and trigger neural plasticity. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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21 pages, 9109 KiB

Open AccessArticle

Online Gait Detection with an Automatic Mobile Trainer Inspired by Neuro-Developmental Treatment

by Fu-Cheng Wang, You-Chi Li, Kai-Lin Wu, Po-Yin Chen and Li-Chen Fu

Sensors 2020, 20(12), 3389; https://doi.org/10.3390/s20123389 - 15 Jun 2020

Cited by 13 | Viewed by 3796

Abstract

This paper demonstrates the development of an automatic mobile trainer employing inertial movement units (IMUs). The device is inspired by Neuro-Developmental Treatment (NDT), which is an effective rehabilitation method for stroke patients that promotes the relearning of motor skills by repeated training. However, [...] Read more.

This paper demonstrates the development of an automatic mobile trainer employing inertial movement units (IMUs). The device is inspired by Neuro-Developmental Treatment (NDT), which is an effective rehabilitation method for stroke patients that promotes the relearning of motor skills by repeated training. However, traditional NDT training is very labor intensive and time consuming for therapists, thus, stroke patients usually cannot receive sufficient rehabilitation training. Therefore, we developed a mobile assisted device that can automatically repeat the therapists’ intervention and help increase patient training time. The proposed mobile trainer, which allows the users to move at their preferred speeds, consists of three systems: the gait detection system, the motor control system, and the movable mechanism. The gait detection system applies IMUs to detect the user’s gait events and triggers the motor control system accordingly. The motor control system receives the triggering signals and imitates the therapist’s intervention patterns by robust control. The movable mechanism integrates these first two systems to form a mobile gait-training device. Finally, we conducted preliminary tests and defined two performance indexes to evaluate the effectiveness of the proposed trainer. Based on the results, the mobile trainer is deemed successful at improving the testing subjects’ walking ability. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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13 pages, 400 KiB

Open AccessArticle

Calibration and Cross-Validation of Accelerometery for Estimating Movement Skills in Children Aged 8–12 Years

by Michael J. Duncan, Alexandra Dobell, Mark Noon, Cain C. T. Clark, Clare M. P. Roscoe, Mark A. Faghy, David Stodden, Ryan Sacko and Emma L. J. Eyre

Sensors 2020, 20(10), 2776; https://doi.org/10.3390/s20102776 - 13 May 2020

Cited by 6 | Viewed by 3694

Abstract

(1) Background: This study sought to calibrate triaxial accelerometery, worn on both wrists, waist and both ankles, during children’s physical activity (PA), with particular attention to object control motor skills performed at a fast and slow cadence, and to cross-validate the accelerometer cut-points [...] Read more.

(1) Background: This study sought to calibrate triaxial accelerometery, worn on both wrists, waist and both ankles, during children’s physical activity (PA), with particular attention to object control motor skills performed at a fast and slow cadence, and to cross-validate the accelerometer cut-points derived from the calibration using an independent dataset. (2) Methods: Twenty boys (10.1 ±1.5 years) undertook seven, five-minute bouts of activity lying supine, standing, running (4.5kmph⁻¹) instep passing a football (fast and slow cadence), dribbling a football (fast and slow cadence), whilst wearing five GENEActiv accelerometers on their non-dominant and dominant wrists and ankles and waist. VO₂ was assessed concurrently using indirect calorimetry. ROC curve analysis was used to generate cut-points representing sedentary, light and moderate PA. The cut-points were then cross-validated using independent data from 30 children (9.4 ± 1.4 years), who had undertaken similar activities whilst wearing accelerometers and being assessed for VO₂. (3) Results: GENEActiv monitors were able to discriminate sedentary activity to an excellent level irrespective of wear location. For moderate PA, discrimination of activity was considered good for monitors placed on the dominant wrist, waist, non-dominant and dominant ankles but fair for the non-dominant wrist. Applying the cut-points to the cross-validation sample indicated that cut-points validated in the calibration were able to successfully discriminate sedentary behaviour and moderate PA to an excellent standard and light PA to a fair standard. (4) Conclusions: Cut-points derived from this calibration demonstrate an excellent ability to discriminate children’s sedentary behaviour and moderate intensity PA comprising motor skill activity. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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12 pages, 3955 KiB

Open AccessArticle

Highly Sensitive E-Textile Strain Sensors Enhanced by Geometrical Treatment for Human Monitoring

by Chi Cuong Vu and Jooyong Kim

Sensors 2020, 20(8), 2383; https://doi.org/10.3390/s20082383 - 22 Apr 2020

Cited by 22 | Viewed by 4895

Abstract

Electronic textiles, also known as smart textiles or smart fabrics, are one of the best form factors that enable electronics to be embedded in them, presenting physical flexibility and sizes that cannot be achieved with other existing electronic manufacturing techniques. As part of [...] Read more.

Electronic textiles, also known as smart textiles or smart fabrics, are one of the best form factors that enable electronics to be embedded in them, presenting physical flexibility and sizes that cannot be achieved with other existing electronic manufacturing techniques. As part of smart textiles, e-sensors for human movement monitoring have attracted tremendous interest from researchers in recent years. Although there have been outstanding developments, smart e-textile sensors still present significant challenges in sensitivity, accuracy, durability, and manufacturing efficiency. This study proposes a two-step approach (from structure layers and shape) to actively enhance the performance of e-textile strain sensors and improve manufacturing ability for the industry. Indeed, the fabricated strain sensors based on the silver paste/single-walled carbon nanotube (SWCNT) layers and buffer cutting lines have fast response time, low hysteresis, and are six times more sensitive than SWCNT sensors alone. The e-textile sensors are integrated on a glove for monitoring the angle of finger motions. Interestingly, by attaching the sensor to the skin of the neck, the pharynx motions when speaking, coughing, and swallowing exhibited obvious and consistent signals. This research highlights the effect of the shapes and structures of e-textile strain sensors in the operation of a wearable e-textile system. This work also is intended as a starting point that will shape the standardization of strain fabric sensors in different applications. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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Review

Jump to: Research, Other

21 pages, 518 KiB

Open AccessReview

Development and Progress in Sensors and Technologies for Human Emotion Recognition

by Shantanu Pal, Subhas Mukhopadhyay and Nagender Suryadevara

Sensors 2021, 21(16), 5554; https://doi.org/10.3390/s21165554 - 18 Aug 2021

Cited by 60 | Viewed by 11811

Abstract

With the advancement of human-computer interaction, robotics, and especially humanoid robots, there is an increasing trend for human-to-human communications over online platforms (e.g., zoom). This has become more significant in recent years due to the Covid-19 pandemic situation. The increased use of online [...] Read more.

With the advancement of human-computer interaction, robotics, and especially humanoid robots, there is an increasing trend for human-to-human communications over online platforms (e.g., zoom). This has become more significant in recent years due to the Covid-19 pandemic situation. The increased use of online platforms for communication signifies the need to build efficient and more interactive human emotion recognition systems. In a human emotion recognition system, the physiological signals of human beings are collected, analyzed, and processed with the help of dedicated learning techniques and algorithms. With the proliferation of emerging technologies, e.g., the Internet of Things (IoT), future Internet, and artificial intelligence, there is a high demand for building scalable, robust, efficient, and trustworthy human recognition systems. In this paper, we present the development and progress in sensors and technologies to detect human emotions. We review the state-of-the-art sensors used for human emotion recognition and different types of activity monitoring. We present the design challenges and provide practical references of such human emotion recognition systems in the real world. Finally, we discuss the current trends in applications and explore the future research directions to address issues, e.g., scalability, security, trust, privacy, transparency, and decentralization. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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25 pages, 752 KiB

Open AccessReview

Effects of Wearable Devices with Biofeedback on Biomechanical Performance of Running—A Systematic Review

by Alexandra Giraldo-Pedroza, Winson Chiu-Chun Lee, Wing-Kai Lam, Robyn Coman and Gursel Alici

Sensors 2020, 20(22), 6637; https://doi.org/10.3390/s20226637 - 19 Nov 2020

Cited by 11 | Viewed by 5406

Abstract

This present review includes a systematic search for peer-reviewed articles published between March 2009 and March 2020 that evaluated the effects of wearable devices with biofeedback on the biomechanics of running. The included articles did not focus on physiological and metabolic metrics. Articles [...] Read more.

This present review includes a systematic search for peer-reviewed articles published between March 2009 and March 2020 that evaluated the effects of wearable devices with biofeedback on the biomechanics of running. The included articles did not focus on physiological and metabolic metrics. Articles with patients, animals, orthoses, exoskeletons and virtual reality were not included. Following the PRISMA guidelines, 417 articles were first identified, and nineteen were selected following the removal of duplicates and articles which did not meet the inclusion criteria. Most reviewed articles reported a significant reduction in positive peak acceleration, which was found to be related to tibial stress fractures in running. Some previous studies provided biofeedback aiming to increase stride frequencies. They produced some positive effects on running, as they reduced vertical load in knee and ankle joints and vertical displacement of the body and increased knee flexion. Some other parameters, including contact ground time and speed, were fed back by wearable devices for running. Such devices reduced running time and increased swing phase time. This article reviews challenges in this area and suggests future studies can evaluate the long-term effects in running biomechanics produced by wearable devices with biofeedback. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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Other

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13 pages, 370 KiB

Open AccessLetter

Lossless Compression of Human Movement IMU Signals

by David Chiasson, Junkai Xu and Peter Shull

Sensors 2020, 20(20), 5926; https://doi.org/10.3390/s20205926 - 20 Oct 2020

Cited by 3 | Viewed by 2422

Abstract

Real-time human movement inertial measurement unit (IMU) signals are central to many emerging medical and technological applications, yet few techniques have been proposed to process and represent this information modality in an efficient manner. In this paper, we explore methods for the lossless [...] Read more.

Real-time human movement inertial measurement unit (IMU) signals are central to many emerging medical and technological applications, yet few techniques have been proposed to process and represent this information modality in an efficient manner. In this paper, we explore methods for the lossless compression of human movement IMU data and compute compression ratios as compared with traditional representation formats on a public corpus of human movement IMU signals for walking, running, sitting, standing, and biking human movement activities. Delta coding was the highest performing compression method which compressed walking, running, and biking data by a factor of 10 and compressed sitting and standing data by a factor of 18 relative to the original CSV formats. Furthermore, delta encoding was shown to approach the a posteriori optimal linear compression level. All methods were implemented and released as open source C code using fixed point computation which can be integrated into a variety of computational platforms. These results could serve to inform and enable human movement data compression in a variety of emerging medical and technological applications. Full article

(This article belongs to the Special Issue Sensor Technology for Improving Human Movements and Postures)

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