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Special Issue "Applications and Development of Intelligent Sensors for Sports, Health, and Medicine"

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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 4950

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Special Issue Editors

Dr. Tomasz Krzeszowski

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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
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Dr. Krzysztof Przednowek

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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
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Dr. Élvio Gouveia

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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
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Prof. Dr. Janusz Iskra

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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 (4 papers)

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Research

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12 pages, 2117 KiB

Open AccessArticle

Unobstructive Heartbeat Monitoring of Sleeping Infants and Young Children Using Sheet-Type PVDF Sensors

and

Sensors 2023, 23(22), 9252; https://doi.org/10.3390/s23229252 - 17 Nov 2023

Viewed by 363

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 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

Open AccessArticle

System for Estimation of Human Anthropometric Parameters Based on Data from Kinect v2 Depth Camera

and

Sensors 2023, 23(7), 3459; https://doi.org/10.3390/s23073459 - 25 Mar 2023

Viewed by 1501

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 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

Open AccessArticle

Development and Practice of Sports-Related Public Welfare Platform Based on Multi-Sensor Technology

and

Sensors 2023, 23(2), 713; https://doi.org/10.3390/s23020713 - 08 Jan 2023

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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 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

Open AccessReview

Inertial Sensors for Hip Arthroplasty Rehabilitation: A Scoping Review

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 1715

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 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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Special Issue "Applications and Development of Intelligent Sensors for Sports, Health, and Medicine"

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