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Sensor Technologies in Sports and Exercise
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Sensor Technologies in Sports and Exercise

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 8010

Special Issue Editors

Dr. Andrea Nicolò

E-Mail Website
Guest Editor
Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Piazza Lauro De Bosis 6, 00135 Rome, Italy
Interests: wearable sensors in sports and exercise; exercise prescription and monitoring in endurance sports; development and validation of training metrics; mechanisms and practical applications underlying the control of breathing during exercise; testing and development of respiratory sensors
Special Issues, Collections and Topics in MDPI journals
Dr. Carlo Massaroni

E-Mail Website
Guest Editor
Unit of Measurement and Biomedical Instrumentation, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 00128 Rome, Italy
Interests: design of wearable systems for non-invasive measurement of respiratory and cardiac parameters; tests of available technologies for non-invasive measurement in the medical field; fiber optics for development of sensors and measuring chains for medical field physiological monitoring; fiber optic sensors for healthcare and industrial applications
Special Issues, Collections and Topics in MDPI journals
Dr. Elena Bergamini

E-Mail Website
Guest Editor
Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Piazza Lauro De Bosis 6, 00135 Rome, Italy
Interests: development and application of methods for the quantification of persons’ motor function; wearable sensors in sports and exercise; clinical gait analysis; wearable technology for clinics and sports applications; motion capture

Special Issue Information

Dear Colleagues,

The field of sports and exercise is experiencing an unprecedented influence of technology on training and competition management and assessment, with important implications for training optimization, health promotion, injury prevention, exercise adherence, healthy lifestyle adoption, fan engagement, and fitness industry development. On the other hand, the challenges offered by different sports disciplines make the technology developed for exercise monitoring suitable for a variety of applications outside of the field of sports, thus outlining the broader impact of sports technology on society. Yet, the needs and demands of sports and exercise require high standards for sensor development, data quality assessment, and computing that are too often unmet both in the fields of research and industry. An example is the ever-increasing diffusion of training metrics that are commonly used before undergoing rigorous validation. Hence, technology may not only represent an advantage, but also a threat to the effective and safe prescription of exercise for different populations. Therefore, this Special Issue aims to collect and promote high-quality research facilitating the use of technology as an asset to health and wellbeing promotion through sports and exercise.

Dr. Andrea Nicolò
Dr. Carlo Massaroni
Dr. Elena Bergamini
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

  • development of sensors and technologies for exercise monitoring
  • validation of signals and metrics recorded with wearable sensors during exercise
  • applications of sensor technologies in sports and exercise
  • performance and health assessment
  • training quantification
  • training load validation and assessment
  • training and performance modeling
  • use of biofeedback in sports and exercise
  • use of technology for improving exercise adherence

Published Papers (5 papers)

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Research

23 pages, 5247 KiB  
Article
Effects of the Flying Start on Estimated Short Sprint Profiles Using Timing Gates
by Mladen Jovanović, Dimitrije Cabarkapa, Håkan Andersson, Dora Nagy, Nenad Trunic, Vladimir Bankovic, Aleksandar Zivkovic, Richard Repasi, Sandor Safar and Laszlo Ratgeber
Sensors 2024, 24(9), 2894; https://doi.org/10.3390/s24092894 - 1 May 2024
Viewed by 441
Abstract
Short sprints are predominantly assessed using timing gates and analyzed through parameters of the mono-exponential equation, including estimated maximal sprinting speed (MSS) and relative acceleration (TAU), derived maximum acceleration (MAC), and relative propulsive maximal power [...] Read more.
Short sprints are predominantly assessed using timing gates and analyzed through parameters of the mono-exponential equation, including estimated maximal sprinting speed (MSS) and relative acceleration (TAU), derived maximum acceleration (MAC), and relative propulsive maximal power (PMAX), further referred to as the No Correction model. However, the frequently recommended flying start technique introduces a bias during parameter estimation. To correct this, two additional models (Estimated TC and Estimated FD) were proposed. To estimate model precision and sensitivity to detect the change, 31 basketball players executed multiple 30 m sprints. Athlete performance was simultaneously measured by a laser gun and timing gates positioned at 5, 10, 20, and 30 m. Short sprint parameters were estimated using a laser gun, representing the criterion measure, and five different timing gate models, representing the practical measures. Only the MSS parameter demonstrated a high agreement between the laser gun and timing gate models, using the percent mean absolute difference (%MAD) estimator (%MAD < 10%). The MSS parameter also showed the highest sensitivity, using the minimum detectable change estimator (%MDC95), with an estimated %MDC95 < 17%. Interestingly, sensitivity was the highest for the No Correction model (%MDC95 < 7%). All other parameters and models demonstrated an unsatisfying level of sensitivity. Thus, sports practitioners should be cautious when using timing gates to estimate maximum acceleration indices and changes in their respective levels. Full article
(This article belongs to the Special Issue Sensor Technologies in Sports and Exercise)
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12 pages, 1327 KiB  
Communication
Validity and Reliability of Polar Team Pro and Playermaker for Estimating Running Distance and Speed in Indoor and Outdoor Conditions
by Simen Sandmæl, Roland van den Tillaar and Terje Dalen
Sensors 2023, 23(19), 8251; https://doi.org/10.3390/s23198251 - 5 Oct 2023
Cited by 1 | Viewed by 1452
Abstract
Although global positioning systems and inertial measurement unit systems are often used to quantify physical variables in training, both types of systems need to be compared, considering their frequent use in measuring physical loads. Thus, the purpose of our study was to test [...] Read more.
Although global positioning systems and inertial measurement unit systems are often used to quantify physical variables in training, both types of systems need to be compared, considering their frequent use in measuring physical loads. Thus, the purpose of our study was to test the reliability and validity of speed and distance run measurements at different intensities in indoor and outdoor conditions made by Polar Team Pro and Playermaker. Four participants (age = 30.0 ± 5.1 years, body mass = 76.3 ± 5.3 kg, height = 1.79 ± 0.09 m), each wearing three Polar Team Pro and two Playermaker sensors, performed 100 m runs with different prescribed intensities (i.e., criterion measure) varying from 8 to 24 km h−1, in a straight line and/or rectangle under indoor and outdoor conditions. Both systems underestimated total distance; Playermaker underestimated speed, the extent of which increased as speed increased, while Polar Team Pro overestimated mean speed at 8 km h−1 for the straight-line condition. No differences emerged in mean speed estimated by Polar Team Pro at any intensities other than 20 km h−1, which was underestimated by 2%. The reliability of the sensors was good, given a coefficient of variation (CV) of <2% for all conditions except when measuring indoor conditions with Polar Team Pro (CV ≈ 10%). Intraclass correlations (ICCs) for consistency within the sensors varied from 0.47 to 0.99, and significantly lower ICCs were documented at 8, 10, and 12 km h−1. Both systems underestimated distance measured in indoor and outdoor conditions, and distance validity in different intensities seemed to worsen as speeds increased. Although Polar Team Pro demonstrated poor validity and reliability in indoor conditions, both systems exhibited good reliability between their sensors in outdoor conditions, whereas the reliability within their sensors varied with different speeds. Full article
(This article belongs to the Special Issue Sensor Technologies in Sports and Exercise)
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18 pages, 1689 KiB  
Article
A Novel Inexpensive Camera-Based Photoelectric Barrier System for Accurate Flying Sprint Time Measurement
by Tom Uhlmann, Sabrina Bräuer, Falk Zaumseil and Guido Brunnett
Sensors 2023, 23(17), 7339; https://doi.org/10.3390/s23177339 - 23 Aug 2023
Viewed by 932
Abstract
This paper introduces a novel approach to addressing the challenge of accurately timing short distance runs, a critical aspect in the assessment of athletic performance. Electronic photoelectric barriers, although recognized for their dependability and accuracy, have remained largely inaccessible to non-professional athletes and [...] Read more.
This paper introduces a novel approach to addressing the challenge of accurately timing short distance runs, a critical aspect in the assessment of athletic performance. Electronic photoelectric barriers, although recognized for their dependability and accuracy, have remained largely inaccessible to non-professional athletes and smaller sport clubs due to their high costs. A comprehensive review of existing timing systems reveals that claimed accuracies beyond 30 ms lack experimental validation across most available systems. To bridge this gap, a mobile, camera-based timing system is proposed, capitalizing on consumer-grade electronics and smartphones to provide an affordable and easily accessible alternative. By leveraging readily available hardware components, the construction of the proposed system is detailed, ensuring its cost-effectiveness and simplicity. Experiments involving track and field athletes demonstrate the proficiency of the proposed system in accurately timing short distance sprints. Comparative assessments against a professional photoelectric cells timing system reveal a remarkable accuracy of 62 ms, firmly establishing the reliability and effectiveness of the proposed system. This finding places the camera-based approach on par with existing commercial systems, thereby offering non-professional athletes and smaller sport clubs an affordable means to achieve accurate timing. In an effort to foster further research and development, open access to the device’s schematics and software is provided. This accessibility encourages collaboration and innovation in the pursuit of enhanced performance assessment tools for athletes. Full article
(This article belongs to the Special Issue Sensor Technologies in Sports and Exercise)
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16 pages, 22986 KiB  
Article
Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning
by Hafeez Ur Rehman Siddiqui, Faizan Younas, Furqan Rustam, Emmanuel Soriano Flores, Julién Brito Ballester, Isabel de la Torre Diez, Sandra Dudley and Imran Ashraf
Sensors 2023, 23(15), 6839; https://doi.org/10.3390/s23156839 - 1 Aug 2023
Cited by 2 | Viewed by 3081
Abstract
Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained [...] Read more.
Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study’s results could help improve coaching techniques and enhance batsmen’s performance in cricket, ultimately improving the game’s overall quality. Full article
(This article belongs to the Special Issue Sensor Technologies in Sports and Exercise)
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21 pages, 10189 KiB  
Article
Flexible Pressure Sensors for Integration into Karate Body Protector
by Derya Tama Birkocak, Pedro Gomes and Helder Carvalho
Sensors 2023, 23(14), 6524; https://doi.org/10.3390/s23146524 - 19 Jul 2023
Cited by 1 | Viewed by 1336
Abstract
The increasing interest in karate has also attracted the attention of researchers, especially in combining the equipment used by practitioners with technology to prevent injuries, improve technical skills and provide appropriate scoring. Contrary to the sport of taekwondo, the development of a smart [...] Read more.
The increasing interest in karate has also attracted the attention of researchers, especially in combining the equipment used by practitioners with technology to prevent injuries, improve technical skills and provide appropriate scoring. Contrary to the sport of taekwondo, the development of a smart body protector in the sport of karate is still a niche field to be researched. This study focused on developing piezoresistive, textile-based pressure sensors using piezoresistive film, conductive fabric as well as different bonding materials and methods. Primarily, small-scale sensors were produced using ultrasonic welding, hot press welding and oven curing. These were characterized using a universal testing machine and specific conditioning and data-acquisition hardware combined with custom processing software. Large-scale sensors were then manufactured to be placed inside the karate body protector and characterized using cyclic testing. The conditioning circuit allows flexible gain adjustment, and it was possible to obtain a stable signal with an output of up to 0.03 V/N, an adequate signal for the tested force range. The transfer function shows some drift over the cycles, in addition to the expected hysteresis and slight nonlinearity, which can be compensated for. Finally, the configuration with the best results was tested in real practice tests; during these tests the body protector was placed on a dummy as well as on a person. The results showed that the piezoresistive textile-based pressure sensor produced is able to detect and quantify the impact of even light punches, providing an unobtrusive means for performance monitoring and score calculation for competitive practice of this sport. Full article
(This article belongs to the Special Issue Sensor Technologies in Sports and Exercise)
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