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Wearable Sensors for Physical Activity Monitoring and Motion Control
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Wearable Sensors for Physical Activity Monitoring and Motion Control

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Wearables".

Deadline for manuscript submissions: 15 August 2024 | Viewed by 21544

Special Issue Editors

Dr. Jesús Fontecha

E-Mail Website
Guest Editor
MAmI Research Lab, Castilla-La Mancha University, 13071 Ciudad Real, Spain
Interests: ubiquitous computing; smart health; mHealth; context awareness; AAL; frailty; gait analysis; data mining; visualization; user interaction
Special Issues, Collections and Topics in MDPI journals
Dr. Iván González

E-Mail Website
Guest Editor
MAmI Research Lab, Castilla-La Mancha University, 13071 Ciudad Real, Spain
Interests: ubiquitous computing; smart health; gait analysis; smart environments; AAL; IoT; sensor networks

Special Issue Information

Dear Colleagues,

Nowadays, there is a mass usage of wearable devices mainly focusing on promoting the healthy lifestyles of users. For example, bracelets and smartwatches have become commercial products well known and sold all over the world. Beyond the use of such devices for monitoring daily exercise, fitness levels and sport activities (sport performance), the last decade has shown an increasing interest in the development of mobile and wearable technologies for health promotion in many different ways. Physical activity monitoring and motion control through wearable technology provide valuable information for rehabilitation purposes, physical and even cognitive assistance. In addition, advances in artificial intelligence and machine learning make it possible to process acquired data from wearable sensors/devices, for instance, to detect postural problems in everyday physical activities (work and home ergonomics), to predict functional decline (early diagnosis and prevention), to identify the risk of falls in elders or, more specifically, to segment, classify and recognize human motion for gait analysis purposes, among others.

This Special Issue is interested in all types of wearable sensors and mobile technologies dedicated to physical activity monitoring and motion control in the domains of healthcare, industry, home, sport, and more.

Dr. Jesús Fontecha
Dr. Iván González
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Low-cost sensors 
  • Motion disorders 
  • Ergonomics 
  • Rehabilitation 
  • Physical assistance 
  • Cognitive assistance 
  • Sport performance 
  • Gait analysis

Published Papers (7 papers)

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Research

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20 pages, 2957 KiB  
Article
Recognition of Human Lower Limb Motion and Muscle Fatigue Status Using a Wearable FES-sEMG System
by Wenbo Zhang, Ziqian Bai, Pengfei Yan, Hongwei Liu and Li Shao
Sensors 2024, 24(7), 2377; https://0-doi-org.brum.beds.ac.uk/10.3390/s24072377 - 08 Apr 2024
Viewed by 416
Abstract
Functional electrical stimulation (FES) devices are widely employed for clinical treatment, rehabilitation, and sports training. However, existing FES devices are inadequate in terms of wearability and cannot recognize a user’s intention to move or muscle fatigue. These issues impede the user’s ability to [...] Read more.
Functional electrical stimulation (FES) devices are widely employed for clinical treatment, rehabilitation, and sports training. However, existing FES devices are inadequate in terms of wearability and cannot recognize a user’s intention to move or muscle fatigue. These issues impede the user’s ability to incorporate FES devices into their daily life. In response to these issues, this paper introduces a novel wearable FES system based on customized textile electrodes. The system is driven by surface electromyography (sEMG) movement intention. A parallel structured deep learning model based on a wearable FES device is used, which enables the identification of both the type of motion and muscle fatigue status without being affected by electrical stimulation. Five subjects took part in an experiment to test the proposed system, and the results showed that our method achieved a high level of accuracy for lower limb motion recognition and muscle fatigue status detection. The preliminary results presented here prove the effectiveness of the novel wearable FES system in terms of recognizing lower limb motions and muscle fatigue status. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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9 pages, 1309 KiB  
Article
A Global Positioning System Used to Monitor the Physical Performance of Elite Beach Handball Referees in a Spanish Championship
by Alejandro Martínez-Rodríguez, Javier Sánchez-Sánchez, Jorge López-Fernández, Daniel Lara-Cobos and Juan Antonio Sánchez-Sáez
Sensors 2024, 24(3), 827; https://0-doi-org.brum.beds.ac.uk/10.3390/s24030827 - 26 Jan 2024
Viewed by 586
Abstract
Beach handball is a fully developed sporting discipline on all five continents which has attracted the attention of researchers in the last decade, resulting in a proliferation of different studies focusing on players but not on referees. The main objective of this cross-sectional [...] Read more.
Beach handball is a fully developed sporting discipline on all five continents which has attracted the attention of researchers in the last decade, resulting in a proliferation of different studies focusing on players but not on referees. The main objective of this cross-sectional research was to determine the physical demands on elite male beach handball referees in four different competitions: U18 male; U18 female; senior male; and senior female. Twelve elite federated male referees (age: 30.86 ± 8 years; body height: 175.72 ± 4.51 cm; body weight: 80.18 ± 17.99 kg; fat percentage: 20.1 ± 4.41%; national or international experience) belonging to the Technical Committee of the Royal Spanish Handball Federation were recruited for this the study. The physical demands required of referees in official matches were measured by installing a GPS device. The sampling frequency used to record their speed and distance was 15 Hz. A triaxial accelerometer (100 Hz) was used to determine their acceleration. An analysis of variance (ANOVA) between competitions with post hoc comparisons using the Bonferroni adjustment was used to compare among categories. A higher distance covered in zone 1 and speeds of 0 to 6 km-h−1 were recorded. Most accelerations and decelerations occurred in zones 0 and 1 (zone 0: 0 to 1 m·s−2; zone 1: 1 to 2 m·s−2). The lack of differences (p > 0.05) between most analysed variables suggest quite similar physical demands of the four analysed competitions. These results provide relevant information to design optimal training plans oriented to the real physical demands on referees in an official competition. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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13 pages, 1539 KiB  
Article
Three-Dimensional Kinematics during Shoulder Scaption in Asymptomatic and Symptomatic Subjects by Inertial Sensors: A Cross-Sectional Study
by Cristina Roldán-Jiménez, Antonio I. Cuesta-Vargas and Jaime Martín-Martín
Sensors 2022, 22(8), 3081; https://0-doi-org.brum.beds.ac.uk/10.3390/s22083081 - 17 Apr 2022
Viewed by 2318
Abstract
Shoulder kinematics is a measure of interest in the clinical setting for diagnosis, evaluating treatment, and quantifying possible changes. The aim was to compare shoulder scaption kinematics between symptomatic and asymptomatic subjects by inertial sensors. Methods: Scaption kinematics of 27 subjects with shoulder [...] Read more.
Shoulder kinematics is a measure of interest in the clinical setting for diagnosis, evaluating treatment, and quantifying possible changes. The aim was to compare shoulder scaption kinematics between symptomatic and asymptomatic subjects by inertial sensors. Methods: Scaption kinematics of 27 subjects with shoulder symptomatology and 16 asymptomatic subjects were evaluated using four inertial sensors placed on the humerus, scapula, forearm, and sternum. Mobility, velocity, and acceleration were obtained from each sensor and the vector norm was calculated from the three spatial axis (x,y,Z). Shoulder function was measured by Upper Limb Functional Index and Disabilities of the Arm, Shoulder, and Hand questionnaires. One way ANOVA was calculated to test differences between the two groups. Effect size was calculated by Cohen’s d with 95% coefficient Intervals. Pearson’s correlation analysis was performed between the vector norms humerus and scapula kinematics against DASH and ULFI results in symptomatic subjects. Results: The asymptomatic group showed higher kinematic values, especially in the humerus and forearm. Symptomatic subjects showed significantly lower values of mobility for scapular protraction-retraction (Cohen’s d 2.654 (1.819–3.489) and anteriorisation-posteriorisation (Cohen’s d 1.195 (0.527–1.863). Values were also lower in symptomatic subjects for velocity in all scapular planes of motion. Negative correlation showed that subjects with higher scores in ULFI or DASH had lower kinematics values. Conclusion: Asymptomatic subjects tend to present greater kinematics in terms of mobility, velocity, and linear acceleration of the upper limb, and lower humerus and scapula kinematics in symptomatic subjects is associated with lower levels of function. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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14 pages, 1462 KiB  
Article
Telehealth Secure Solution to Provide Childhood Obesity Monitoring
by Elitania Jiménez-García, Miguel Ángel Murillo-Escobar, Jesús Fontecha-Diezma, Rosa Martha López-Gutiérrez and Liliana Cardoza-Avendaño
Sensors 2022, 22(3), 1213; https://0-doi-org.brum.beds.ac.uk/10.3390/s22031213 - 05 Feb 2022
Cited by 2 | Viewed by 2723
Abstract
Childhood obesity causes not only medical and psychosocial problems, it also reduces the life expectancy of the adults that they will become. On a large scale, obese adults adversely affect labor markets and the gross domestic product of countries. Monitoring the growth charts [...] Read more.
Childhood obesity causes not only medical and psychosocial problems, it also reduces the life expectancy of the adults that they will become. On a large scale, obese adults adversely affect labor markets and the gross domestic product of countries. Monitoring the growth charts of children helps to maintain their body weight within healthy parameters according to the World Health Organization. Modern technologies allow the use of telehealth to carry out weight control programs and monitoring to verify children’s compliance with the daily recommendations for risk factors that can be promoters of obesity, such as insufficient physical activity and insufficient sleep hours. In this work, we propose a secure remote monitoring and supervision scheme of physical activity and sleep hours for the children based on telehealth, multi-user networks, chaotic encryption, and spread spectrum, which, to our knowledge, is the first attempt to consider this service for safe pediatric telemedicine. In experimental results, we adapted a recent encryption algorithm in the literature for the proposed monitoring scheme using the assessment of childhood obesity as an application case in a multi-user network to securely send and receive fictitious parameters on childhood obesity of five users through the Internet by using just one communication channel. The results show that all the monitored parameters can be transmitted securely, achieving high sensitivity against secret key, enough secret key space, high resistance against noise interference, and 4.99 Mb/sec in computational simulations. The proposed scheme can be used to monitor childhood obesity in secure telehealth application. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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14 pages, 5074 KiB  
Article
Recognizing Physical Activities for Spinal Cord Injury Rehabilitation Using Wearable Sensors
by Nora Alhammad and Hmood Al-Dossari
Sensors 2021, 21(16), 5479; https://0-doi-org.brum.beds.ac.uk/10.3390/s21165479 - 14 Aug 2021
Cited by 2 | Viewed by 3088
Abstract
The research area of activity recognition is fast growing with diverse applications. However, advances in this field have not yet been used to monitor the rehabilitation of individuals with spinal cord injury. Noteworthily, relying on patient surveys to assess adherence can undermine the [...] Read more.
The research area of activity recognition is fast growing with diverse applications. However, advances in this field have not yet been used to monitor the rehabilitation of individuals with spinal cord injury. Noteworthily, relying on patient surveys to assess adherence can undermine the outcomes of rehabilitation. Therefore, this paper presents and implements a systematic activity recognition method to recognize physical activities applied by subjects during rehabilitation for spinal cord injury. In the method, raw sensor data are divided into fragments using a dynamic segmentation technique, providing higher recognition performance compared to the sliding window, which is a commonly used approach. To develop the method and build a predictive model, a machine learning approach was adopted. The proposed method was evaluated on a dataset obtained from a single wrist-worn accelerometer. The results demonstrated the effectiveness of the proposed method in recognizing all of the activities that were examined, and it achieved an overall accuracy of 96.86%. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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Review

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17 pages, 3259 KiB  
Review
Recent Advances in Flexible Sensors and Their Applications
by Bouchaib Zazoum, Khalid Mujasam Batoo and Muhammad Azhar Ali Khan
Sensors 2022, 22(12), 4653; https://0-doi-org.brum.beds.ac.uk/10.3390/s22124653 - 20 Jun 2022
Cited by 33 | Viewed by 9856
Abstract
Flexible sensors are low cost, wearable, and lightweight, as well as having a simple structure as per the requirements of engineering applications. Furthermore, for many potential applications, such as human health monitoring, robotics, wearable electronics, and artificial intelligence, flexible sensors require high sensitivity [...] Read more.
Flexible sensors are low cost, wearable, and lightweight, as well as having a simple structure as per the requirements of engineering applications. Furthermore, for many potential applications, such as human health monitoring, robotics, wearable electronics, and artificial intelligence, flexible sensors require high sensitivity and stretchability. Herein, this paper systematically summarizes the latest progress in the development of flexible sensors. The review briefly presents the state of the art in flexible sensors, including the materials involved, sensing mechanisms, manufacturing methods, and the latest development of flexible sensors in health monitoring and soft robotic applications. Moreover, this paper provides perspectives on the challenges in this field and the prospect of flexible sensors. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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Other

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0 pages, 471 KiB  
Systematic Review
Transparency as a Means to Analyse the Impact of Inertial Sensors on Users during the Occupational Ergonomic Assessment: A Systematic Review
by Marco A. García-Luna, Daniel Ruiz-Fernández, Juan Tortosa-Martínez, Carmen Manchado, Miguel García-Jaén and Juan M. Cortell-Tormo
Sensors 2024, 24(1), 298; https://0-doi-org.brum.beds.ac.uk/10.3390/s24010298 - 04 Jan 2024
Viewed by 889
Abstract
The literature has yielded promising data over the past decade regarding the use of inertial sensors for the analysis of occupational ergonomics. However, despite their significant advantages (e.g., portability, lightness, low cost, etc.), their widespread implementation in the actual workplace has not yet [...] Read more.
The literature has yielded promising data over the past decade regarding the use of inertial sensors for the analysis of occupational ergonomics. However, despite their significant advantages (e.g., portability, lightness, low cost, etc.), their widespread implementation in the actual workplace has not yet been realized, possibly due to their discomfort or potential alteration of the worker’s behaviour. This systematic review has two main objectives: (i) to synthesize and evaluate studies that have employed inertial sensors in ergonomic analysis based on the RULA method; and (ii) to propose an evaluation system for the transparency of this technology to the user as a potential factor that could influence the behaviour and/or movements of the worker. A search was conducted on the Web of Science and Scopus databases. The studies were summarized and categorized based on the type of industry, objective, type and number of sensors used, body parts analysed, combination (or not) with other technologies, real or controlled environment, and transparency. A total of 17 studies were included in this review. The Xsens MVN system was the most widely used in this review, and the majority of studies were classified with a moderate level of transparency. It is noteworthy, however, that there is a limited and worrisome number of studies conducted in uncontrolled real environments. Full article
(This article belongs to the Special Issue Wearable Sensors for Physical Activity Monitoring and Motion Control)
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