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Applications and Development of Intelligent Sensors for Sports, Health, and Medicine

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

Deadline for manuscript submissions: 20 May 2024 | Viewed by 8868

Special Issue Editors

Dr. Tomasz Krzeszowski

E-Mail Website
Guest Editor
Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszow, Poland
Interests: human motion tracking; human body pose estimation; particle swarm optimization; parallel and distributed computing; gait recognition
Special Issues, Collections and Topics in MDPI journals
Dr. Krzysztof Przednowek

E-Mail Website
Guest Editor
Institute of Physical Culture Sciences, Medical College of Rzeszów University, Rzeszów University, 35-959 Rzeszów, Poland
Interests: sports biomechanics; human movement analysis; computer science in sports; sports prediction
Special Issues, Collections and Topics in MDPI journals
Dr. Élvio Gouveia

E-Mail Website1 Website2
Guest Editor
Department of Physical Education and Sport, University of Madeira, 9020-105 Funchal, Portugal
Interests: functional fitness; cognitive function; quality of life; physical activity; physical education; interactive technologies
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Janusz Iskra

E-Mail Website
Guest Editor
Faculty of Physical Education and Physiotherapy, Opole University of Technology, ul. Prószkowska 76, 45-758 Opole, Poland
Interests: sport sciences; sports training; sports biomechanics; physical fitness; strength and condition

Special Issue Information

Dear Colleagues,

Currently, the application and development of various types of intelligent sensors in sports, health, and medicine are one of the most interesting and active research topics. Smart sensors play a significant role in assessing various health, medical, and sports indicators. Motion analysis using cameras, depth sensors, IMU sensors, or EMG technology is effectively used to evaluate human movement in many areas of life. In professional sports, intelligent sensors have revolutionized the training process. Examples include sensors with built-in GPS modules to monitor the player’s locomotor intensity during a match or training. Based on sensor data, individual training units are optimized. Another important aspect of using smart sensors is the direct assessment of physical activity. Using accelerometers, it is possible to objectively assess and monitor the intensity of physical activity levels among children, adolescents, adults, and older adults. That information is essential to deliver the most effective exercise training programs according to the people's needs. Various types of sensors can also be used to diagnose disease entities, e.g. motion capture systems can be used to assess diseases of the musculoskeletal system. We welcome for submission of high-quality publications of researchers who work on applications and development of various types of sensors for sports, health, and medicine. More precisely, the relevant topics for this special issue include (but are not limited to):

  • Human motion analysis
  • Sensors in biomechanics
  • Assessing physical fitness and physical activities
  • Sensors in athletic training
  • Sensors in kinesiology
  • Sensors in sleep analysis
  • Sensors in strength and conditioning
  • Human pose estimation
  • Multi-person pose estimation
  • Sport players tracking
  • Action and gesture recognition
  • Gait recognition
  • Human fall detection

Dr. Tomasz Krzeszowski
Dr. Krzysztof Przednowek
Dr. Élvio Gouveia
Prof. Dr. Janusz Iskra
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

  • human movement
  • sports biomechanics
  • sport sciences
  • GPS tracking
  • health science
  • multi-person 3D pose estimation
  • human fall detection
  • gait recognition
  • human motion tracking

Published Papers (6 papers)

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Research

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13 pages, 1572 KiB  
Article
Multibody Model with Foot-Deformation Approach for Estimating Ground Reaction Forces and Moments and Joint Torques during Level Walking through Optical Motion Capture without Optimization Techniques
by Naoto Haraguchi and Kazunori Hase
Sensors 2024, 24(9), 2792; https://doi.org/10.3390/s24092792 (registering DOI) - 27 Apr 2024
Abstract
The biomechanical-model-based approach with a contact model offers advantages in estimating ground reaction forces (GRFs) and ground reaction moments (GRMs), as it does not rely on the need for training data and gait assumptions. However, this approach faces the challenge of long computational [...] Read more.
The biomechanical-model-based approach with a contact model offers advantages in estimating ground reaction forces (GRFs) and ground reaction moments (GRMs), as it does not rely on the need for training data and gait assumptions. However, this approach faces the challenge of long computational times due to the inclusion of optimization processes. To address this challenge, the present study developed a new optical motion capture (OMC)-based method to estimate GRFs, GRMs, and joint torques without prolonged computational times. The proposed approach performs the estimation process by distributing external forces, as determined by a multibody model, between the left and right feet based on foot deformations, thereby predicting the GRFs and GRMs without relying on optimization techniques. In this study, prediction accuracies during level walking were confirmed by comparing a general analysis using a force plate with the estimation results. The comparison revealed excellent or strong correlations between the prediction and the measurements for all GRFs, GRMs, and lower-limb-joint torques. The proposed method, which provides practical estimation with low computational cost, facilitates efficient biomechanical analysis and rapid feedback of analysis results, contributing to its increased applicability in clinical settings. Full article
(This article belongs to the Special Issue Applications and Development of Intelligent Sensors for Sports, Health, and Medicine)
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14 pages, 682 KiB  
Article
Ebbing Strength, Fading Power: Unveiling the Impact of Persistent Fatigue on Muscle Performance in COVID-19 Survivors
by Mateusz Kowal, Ewa Morgiel, Sławomir Winiarski, Robert Dymarek, Weronika Bajer, Marta Madej, Agata Sebastian, Marcin Madziarski, Nicole Wedel, Krzysztof Proc, Katarzyna Madziarska, Piotr Wiland and Małgorzata Paprocka-Borowicz
Sensors 2024, 24(4), 1250; https://doi.org/10.3390/s24041250 - 15 Feb 2024
Viewed by 1354
Abstract
The total number of confirmed cases of COVID-19 caused by SARS-CoV-2 virus infection is over 621 million. Post-COVID-19 syndrome, also known as long COVID or long-haul COVID, refers to a persistent condition where individuals experience symptoms and health issues after the acute phase [...] Read more.
The total number of confirmed cases of COVID-19 caused by SARS-CoV-2 virus infection is over 621 million. Post-COVID-19 syndrome, also known as long COVID or long-haul COVID, refers to a persistent condition where individuals experience symptoms and health issues after the acute phase of COVID-19. The aim of this study was to assess the strength and fatigue of skeletal muscles in people recovered from COVID-19. A total of 94 individuals took part in this cross-sectional study, with 45 participants (referred to as the Post-COVID Cohort, PCC) and 49 healthy age-matched volunteers (Healthy Control Cohort, HCC). This research article uses the direct dynamometry method to provide a detailed analysis of post-COVID survivors’ strength and power characteristics. The Biodex System 4 Pro was utilized to evaluate muscle strength characteristics during the fatigue test. The fatigue work in extensors and flexors was significantly higher in the PCC. The PCC also showed significantly less power in both extensors and flexors compared to the HCC. In conclusion, this study provides compelling evidence of the impact of post-COVID-19 fatigue on muscle performance, highlighting the importance of considering these effects in the rehabilitation and care of individuals recovering from the virus. PCC achieved lower muscle strength values than HCC. Full article
(This article belongs to the Special Issue Applications and Development of Intelligent Sensors for Sports, Health, and Medicine)
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12 pages, 2117 KiB  
Article
Unobstructive Heartbeat Monitoring of Sleeping Infants and Young Children Using Sheet-Type PVDF Sensors
by Daisuke Kumaki, Yuko Motoshima, Fujio Higuchi, Katsuhiro Sato, Tomohito Sekine and Shizuo Tokito
Sensors 2023, 23(22), 9252; https://doi.org/10.3390/s23229252 - 17 Nov 2023
Viewed by 978
Abstract
Techniques for noninvasively acquiring the vital information of infants and young children are considered very useful in the fields of healthcare and medical care. An unobstructive measurement method for sleeping infants and young children under the age of 6 years using a sheet-type [...] Read more.
Techniques for noninvasively acquiring the vital information of infants and young children are considered very useful in the fields of healthcare and medical care. An unobstructive measurement method for sleeping infants and young children under the age of 6 years using a sheet-type vital sensor with a polyvinylidene fluoride (PVDF) pressure-sensitive layer is demonstrated. The signal filter conditions to obtain the ballistocardiogram (BCG) and phonocardiogram (PCG) are discussed from the waveform data of infants and young children. The difference in signal processing conditions was caused by the physique of the infants and young children. The peak-to-peak interval (PPI) extracted from the BCG or PCG during sleep showed an extremely high correlation with the R-to-R interval (RRI) extracted from the electrocardiogram (ECG). The vital changes until awakening in infants monitored using a sheet sensor were also investigated. In infants under one year of age that awakened spontaneously, the distinctive vital changes during awakening were observed. Understanding the changes in the heartbeat and respiration signs of infants and young children during sleep is essential for improving the accuracy of abnormality detection by unobstructive sensors. Full article
(This article belongs to the Special Issue Applications and Development of Intelligent Sensors for Sports, Health, and Medicine)
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12 pages, 2319 KiB  
Article
System for Estimation of Human Anthropometric Parameters Based on Data from Kinect v2 Depth Camera
by Tomasz Krzeszowski, Bartosz Dziadek, Cíntia França, Francisco Martins, Élvio Rúbio Gouveia and Krzysztof Przednowek
Sensors 2023, 23(7), 3459; https://doi.org/10.3390/s23073459 - 25 Mar 2023
Viewed by 2272
Abstract
Anthropometric measurements of the human body are an important problem that affects many aspects of human life. However, anthropometric measurement often requires the application of an appropriate measurement procedure and the use of specialized, sometimes expensive measurement tools. Sometimes the measurement procedure is [...] Read more.
Anthropometric measurements of the human body are an important problem that affects many aspects of human life. However, anthropometric measurement often requires the application of an appropriate measurement procedure and the use of specialized, sometimes expensive measurement tools. Sometimes the measurement procedure is complicated, time-consuming, and requires properly trained personnel. This study aimed to develop a system for estimating human anthropometric parameters based on a three-dimensional scan of the complete body made with an inexpensive depth camera in the form of the Kinect v2 sensor. The research included 129 men aged 18 to 28. The developed system consists of a rotating platform, a depth sensor (Kinect v2), and a PC computer that was used to record 3D data, and to estimate individual anthropometric parameters. Experimental studies have shown that the precision of the proposed system for a significant part of the parameters is satisfactory. The largest error was found in the waist circumference parameter. The results obtained confirm that this method can be used in anthropometric measurements. Full article
(This article belongs to the Special Issue Applications and Development of Intelligent Sensors for Sports, Health, and Medicine)
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13 pages, 1628 KiB  
Article
Development and Practice of Sports-Related Public Welfare Platform Based on Multi-Sensor Technology
by Quantao He, Tongchang Hu, Yong Zhong, Wenjuan Li and Ren Sun
Sensors 2023, 23(2), 713; https://doi.org/10.3390/s23020713 - 08 Jan 2023
Viewed by 1154
Abstract
Today, more and more Internet public media platforms allowing people to make donations or seek help are being founded in China. However, there are few specialized sports-related public welfare platforms. In this paper, a sports-related public welfare platform that aims to help people [...] Read more.
Today, more and more Internet public media platforms allowing people to make donations or seek help are being founded in China. However, there are few specialized sports-related public welfare platforms. In this paper, a sports-related public welfare platform that aims to help people who were disabled due to participation in sports and those who are disabled but want to participate in sports was developed based on multi-sensor technology. A multi-sensor data fusion algorithm was developed, and its estimation performance was verified by comparing it with the existing Kalman consistent filtering algorithm in terms of average estimation and average consistency errors. Experimental results prove that the speed of the data collection and analysis of the sports-related public welfare platform using the algorithm established in this paper was greatly improved. Relevant data on how users used this platform showed that various factors affected users’ practical satisfaction with sports-related public welfare media platforms. It is suggested that a sports-related public welfare media platform should pay attention to the aid effect, and specific efforts should be devoted to improving the reliability and timeliness of public welfare aid information, and ensuring the stability of the platform system. Full article
(This article belongs to the Special Issue Applications and Development of Intelligent Sensors for Sports, Health, and Medicine)
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Review

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25 pages, 2345 KiB  
Review
Inertial Sensors for Hip Arthroplasty Rehabilitation: A Scoping Review
by Patricia Acosta-Vargas, Omar Flor, Belén Salvador-Acosta, Franyelit Suárez-Carreño, Marco Santórum, Santiago Solorzano and Luis Salvador-Ullauri
Sensors 2023, 23(11), 5048; https://doi.org/10.3390/s23115048 - 25 May 2023
Cited by 1 | Viewed by 2445
Abstract
The objective of this scoping review is to characterize the current panorama of inertia sensors for the rehabilitation of hip arthroplasty. In this context, the most widely used sensors are IMUs, which combine accelerometers and gyroscopes to measure acceleration and angular velocity in [...] Read more.
The objective of this scoping review is to characterize the current panorama of inertia sensors for the rehabilitation of hip arthroplasty. In this context, the most widely used sensors are IMUs, which combine accelerometers and gyroscopes to measure acceleration and angular velocity in three axes. We found that data collected by the IMU sensors are used to analyze and detect any deviation from the normal to measure the position and movement of the hip joint. The main functions of inertial sensors are to measure various aspects of training, such as speed, acceleration, and body orientation. The reviewers extracted the most relevant articles published between 2010 and 2023 in the ACM Digital Library, PubMed, ScienceDirect, Scopus, and Web of Science. In this scoping review, the PRISMA-ScR checklist was used, and a Cohen’s kappa coefficient of 0.4866 was applied, implying moderate agreement between reviewers; 23 primary studies were extracted from a total of 681. In the future, it will be an excellent challenge for experts in inertial sensors with medical applications to provide access codes for other researchers, which will be one of the most critical trends in the advancement of applications of portable inertial sensors for biomechanics. Full article
(This article belongs to the Special Issue Applications and Development of Intelligent Sensors for Sports, Health, and Medicine)
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