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Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance

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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: closed (20 December 2020) | Viewed by 50386

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Special Issue Editors

Prof. Dr. Justin Jeon

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Guest Editor

Department of Sport Industry Studies, Yonsei University, Seoul 03722, Korea
Interests: physical activity; exercise physiology
Special Issues, Collections and Topics in MDPI journals

Dr. Seonug Jae Yoo

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Guest Editor

Advanced Sensor Development Team, Samsung Electronics
Interests: biometric sensors; 3D depth sensor

Special Issue Information

Dear Colleagues,

During exercise and sport activity, massive joint and muscle movements occur which result in hormonal, cardiopulmonary, and metabolic response. Repetitive participation of exercise and sport activity further results in the improvement of neuromuscular coordination, increase in muscle mass, strength, and power, as well as cardiopulmonary fitness. Traditionally, assessment of physical activity and cardiopulmonary and musculoskeletal fitness require very expensive devices, such as metabolic carts, dynamometers (Cybex and Contrax), and accelerometers (Actigraph). Measurement of movement, physical activity, and fitness levels provide valuable information to predict a person’s health, physical function, and risk of different musculoskeletal and metabolic diseases, such as low back pain, osteoarthritis, shoulder joint problem, diabetes, cardiovascular disease, and even cancer risk. Furthermore, these types of information also provide postural, kinematic, and biomechanical information during sport activity, which may predict the sports performance of participants. On the other hand, the advances in artificial intelligence (AI) and machine learning (ML) provide new ways to interact and gain insights into the captured data, which enable analyzing, segmenting, classifying, and recognizing human posture/movement and cardiopulmonary response to exercise and physical and sport activities.

This Special Issue will cover a wide range of topics around exercise and physical and sport activities, including new sensor technologies to capture movement, musculoskeletal/cardiopulmonary response to exercise/physical and sport activities, the application prospect of sensors in exercise and sport activities. and new algorithmic approaches to derive, analyze, and recognize exercise and physical activity sensor data.

Prof. Dr. Justin Jeon
Dr. Seonug Jae Yoo
Guest Editors

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Keywords

Exercise
Physical activity
Health promotion
Sports performance

Published Papers (13 papers)

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Research

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12 pages, 1346 KiB

Open AccessArticle

Machine Learning Algorithms for Activity-Intensity Recognition Using Accelerometer Data

by Eduardo Gomes, Luciano Bertini, Wagner Rangel Campos, Ana Paula Sobral, Izabela Mocaiber and Alessandro Copetti

Sensors 2021, 21(4), 1214; https://doi.org/10.3390/s21041214 - 09 Feb 2021

Cited by 10 | Viewed by 3202

Abstract

In pervasive healthcare monitoring, activity recognition is critical information for adequate management of the patient. Despite the great number of studies on this topic, a contextually relevant parameter that has received less attention is intensity recognition. In the present study, we investigated the potential advantage of coupling activity and intensity, namely, Activity-Intensity, in accelerometer data to improve the description of daily activities of individuals. We further tested two alternatives for supervised classification. In the first alternative, the activity and intensity are inferred together by applying a single classifier algorithm. In the other alternative, the activity and intensity are classified separately. In both cases, the algorithms used for classification are k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF). The results showed the viability of the classification with good accuracy for Activity-Intensity recognition. The best approach was KNN implemented in the single classifier alternative, which resulted in 79% of accuracy. Using two classifiers, the result was 97% accuracy for activity recognition (Random Forest), and 80% for intensity recognition (KNN), which resulted in 78% for activity-intensity coupled. These findings have potential applications to improve the contextualized evaluation of movement by health professionals in the form of a decision system with expert rules. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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9 pages, 649 KiB

Open AccessCommunication

Managing Vibration Training Safety by Using Knee Flexion Angle and Rating Perceived Exertion

by Long-Ren Chuang, Wen-Wen Yang, Po-Ling Chang, Vincent Chiun-Fan Chen, Chiang Liu and Tzyy-Yuang Shiang

Sensors 2021, 21(4), 1158; https://doi.org/10.3390/s21041158 - 07 Feb 2021

Cited by 4 | Viewed by 2798

Abstract

Whole-body vibration (WBV) is commonly applied in exercise and rehabilitation and its safety issues have been a major concern. Vibration measured using accelerometers can be used to further analyze the vibration transmissibility. Optimal bending angles and rating of perceived exertion (RPE) evaluations have not been sufficiently explored to mitigate the adverse effect. Therefore, the aims of this study were to investigate the effect of various knee flexion angles on the transmissibility to the head and knee, the RPE during WBV exposure, and the link between the transmissibility to the head and the RPE. Sixteen participants randomly performed static squats with knee flexion angles of 90, 110, 130, and 150 degrees on a WBV platform. Three accelerometers were fixed on the head, knee, and center of the vibration platform to provide data of platform-to-head and platform-to-knee transmissibilities. The results showed that the flexion angle of 110 degrees induced the lowest platform-to-head transmissibility and the lowest RPE (p < 0.01). A positive correlation between RPE and the platform-to-head transmissibility was observed. This study concluded that a knee flexion of about 110 degrees is most appropriate for reducing vibration transmissibility. The reported RPE could be used to reflect the vibration impact to the head. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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9 pages, 1335 KiB

Open AccessCommunication

Positional Differences in Pre-Season Scrimmage Performance of Division I Collegiate Football Players

by Kate S. Early, Nathan P. Lemoine, Annie Simoneaux, Shelly Mullenix, Jack Marucci, Michael J. MacLellan and Neil M. Johannsen

Sensors 2021, 21(3), 769; https://doi.org/10.3390/s21030769 - 24 Jan 2021

Cited by 1 | Viewed by 1652

Abstract

This study aimed to describe the physical demands of American football players using novel performance analysis techniques. Heart rate (HR) and accelerometer-based activity levels were observed across two pre-season scrimmages in 23 Division I collegiate football players (age: 19 ± 1 y, height: 1.90 ± 0.06 m, weight: 116.2 ± 19.4 kg). Data were analyzed using a MATLAB program and inter-rater reproducibility assessed using inter-class correlations (ICC). Players were analyzed by side (offense/defense) and position (skill/non-skill). Performance variables assessed in bursts of activity included burst duration, HR_mean and HR_max (bpm), and mean activity (vector magnitude units [vmu]). Exercise intensity was categorized as time spent in % HRmax in 5% increments. The burst duration (8.1±3.9 min, ICC = 0.72), HR_mean (157 ± 12 bpm, ICC = 0.96) and mean activity (0.30 ± 0.05 vmu, ICC = 0.86) were reproducible. HR_mean (p = 0.05) and HR_max (p = 0.001) were greater on defense. Offense spent more time at 65–70% HR_max (p = 0.01), 70–75% HR_max (p = 0.02) while defense spent more time 90–95% HR_max and ≥95% HR_max (p = 0.03). HR_mean (p = 0.70) and HR_peak (p = 0.80) were not different between positions across both sides. Skilled players demonstrated greater mean activity (p = 0.02). The sport-specific analysis described HR and activity level in a reproducible manner. Automated methods of assessing HR may be useful in training and game time performance but ultimately provides support to coaching decision making. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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11 pages, 1759 KiB

Open AccessArticle

Performance Analysis in Olympic Sailors of the Formula Kite Class Using GPS

by Israel Caraballo, José Luis González-Montesinos, Francisco Casado-Rodríguez and José V. Gutierrez-Manzanedo

Sensors 2021, 21(2), 574; https://doi.org/10.3390/s21020574 - 15 Jan 2021

Cited by 6 | Viewed by 2785

Abstract

Formula Kite is an Olympic sport that mainly differs from other kitesurfing modalities for the use of a hydrofoil. It is considered an extreme sport due to the great technical ability required. Regarding performance, the variables that determine performance in a real competition situation have not been studied, and even less so with Olympic sailors. Therefore, the objective of this study was to determine the technical and tactical variables that differentiate elite sailors. The sample consisted of 42 Olympic sailors of the Formula Kite class, who were evaluated in three World Cups. Using a GPS device, the speed, distance traveled, maneuvers, and time spent on the courses of upwind, downwind, and beam reach were recorded. The highest-level sailors presented a higher speed in upwind/downwind/beam reach and a shorter time in upwind and beam reach. Performance seems to be more strongly influenced by technical variables, such as speed, than by tactical variables. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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11 pages, 2604 KiB

Open AccessArticle

Influence of Strength Level on the Acute Post-Activation Performance Enhancement Following Flywheel and Free Weight Resistance Training

by Borja Sañudo, Moisés de Hoyo, G Gregory Haff and Alejandro Muñoz-López

Sensors 2020, 20(24), 7156; https://doi.org/10.3390/s20247156 - 14 Dec 2020

Cited by 9 | Viewed by 3180

Abstract

This study aimed to compare the post-activation potentiation performance enhancement (PAPE) response to the acute inertial flywheel (FW) and free weight resistance training (TRA) on subsequent countermovement jump (CMJ) and sprint performance (10 m sprint). This study used a randomized crossover design including twenty-eight healthy males that were divided into strong (relative one-repetition maximum (1RM) back squat > 2.0 × body mass) and weak (relative 1RM back squat < 2.0 × body mass) groups. All participants performed the following: (a) three reps at 90% of their 1RM back squat (TRA) and (b) three reps on an inertial FW (plus one repetition to initiate flywheel movement) with an intensity that generated a mean propulsive velocity equal to that achieved with 90% of the 1RM back squat. Before and after the conditioning activity, participants performed two CMJs and two 10 m sprints. Within-group analyses showed significantly greater CMJ (d > 0.9, p < 0.001) and sprint performance (d > 0.5, p < 0.05) in the FW and the TRA group. Between-group analysis showed that sprint changes were significantly greater in the FW-strong group when compared with the TRA (F_1,18 = 5.11, p = 0.036, η²_p = 0.221—large) group. These results suggest that using a squat activation protocol on a FW may lead to an acute positive effect on jump and sprint performance, especially in stronger individuals. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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28 pages, 3223 KiB

Open AccessArticle

Health Promotion for Childhood Obesity: An Approach Based on Self-Tracking of Data

by Nazaret Gómez-del-Río, Carina S. González-González, Pedro A. Toledo-Delgado, Vanesa Muñoz-Cruz and Francisco García-Peñalvo

Sensors 2020, 20(13), 3778; https://doi.org/10.3390/s20133778 - 06 Jul 2020

Cited by 12 | Viewed by 6226

Abstract

At present, obesity and overweight are a global health epidemic. Traditional interventions for promoting healthy habits do not appear to be effective. However, emerging technological solutions based on wearables and mobile devices can be useful in promoting healthy habits. These applications generate a considerable amount of tracked activity data. Consequently, our approach is based on the quantified-self model for recommending healthy activities. Gamification can also be used as a mechanism to enhance personalization, increasing user motivation. This paper describes the quantified-self model and its data sources, the activity recommender system, and the PROVITAO App user experience model. Furthermore, it presents the results of a gamified program applied for three years in children with obesity and the process of evaluating the quantified-self model with experts. Positive outcomes were obtained in children’s medical parameters and health habits. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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10 pages, 919 KiB

Open AccessArticle

Changes in Muscle Contractile Properties after Cold- or Warm-Water Immersion Using Tensiomyography: A Cross-Over Randomised Trial

by Esther Mur Gimeno, Francesco Campa, Georgian Badicu, Jorge Castizo-Olier, Elisabet Palomera-Fanegas and Raquel Sebio-Garcia

Sensors 2020, 20(11), 3193; https://doi.org/10.3390/s20113193 - 04 Jun 2020

Cited by 5 | Viewed by 3943

Abstract

Muscle contractile properties in clinical practice are often measured using either subjective scales or high-cost, inaccessible equipment. In this randomised cross-over study, we aimed to explore the use of tensiomyography (TMG) to assess changes in muscle contractile properties after cold- and warm-water immersion. The muscle contractile properties of the biceps femoris (BF) were assessed using TMG in 12 healthy active men (mean age 23 ± 3 years, Body Mass Index 22.9 ± 1.3 kg/m²) before and after a 20-min warm- or cold-water immersion over a period of 40 min. Muscle displacement (Dm) and contraction time (Tc) were registered as the main variables of the study. There was a significant condition by time interaction for Dm (p < 0.01). Post hoc analysis showed that, compared to the baseline, there was an increase in Dm 40 min after warm-water immersion (p < 0.01) and a decrease at 10 min after cold-water immersion (p < 0.01). No significant effect was found for Tc. Our results indicate that muscle contractile properties are affected by water temperature and time after the immersion; therefore, these factors should be taken into account when water-immersion is used as a recovery strategy. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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11 pages, 1956 KiB

Open AccessArticle

A Proposed Method to Assess the Mechanical Properties of Treadmill Surfaces

by Enrique Colino, Jorge Garcia-Unanue, Bas Van Hooren, Leonor Gallardo, Kenneth Meijer, Alejandro Lucia and Jose Luis Felipe

Sensors 2020, 20(9), 2724; https://doi.org/10.3390/s20092724 - 10 May 2020

Cited by 3 | Viewed by 5130

Abstract

The aim of this study was to define a reliable and sensitive test method for assessing Shock Absorption (SA), Vertical Deformation (VD), and Energy Restitution (ER) in treadmill surfaces. A total of 42 treadmills belonging to four different models were included in the study: (a) Technogym Jog700 Excite (n = 10), (b) Technogym Artis Run (n = 12), (c) LifeFitness Integrity Series 97T (n = 11), and (d) LifeFitness Integrity Series DX (n = 9). An advanced artificial athlete (AAA) device was used to assess SA, VD, and ER at three different locations along the longitudinal axis of each treadmill and in the support area of the athletes’ feet. For each location, our results show that the error assumed when performing one impact with the AAA instead of three (SA ≤ |0.1|%, VD ≤ |0.0| mm, and ER ≤ |0.2|%) is lower than the smallest changes that can be detected by the measuring device (SA = 0.4%, VD = 0.2 mm, and ER = 0.9%). Also, our results show the ability of the test method to detect meaningful differences between locations once the one-impact criterium is adopted, since absolute minimum differences between zones (SA: |0.6|%, VD: |0.3| mm, and ER: |1.2|%) were above the uncertainty of the measuring device. Therefore, performing a single impact with the AAA in each of the three locations described in this study can be considered a representative and reliable method for assessing SA, VD, and ER in treadmill surfaces. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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17 pages, 4711 KiB

Open AccessArticle

Automatic Registration of Footsteps in Contact Regions for Reactive Agility Training in Sports

by Eduardo C. Latorre, Marcos D. Zuniga, Enrique Arriaza, Fabian Moya and Christopher Nikulin

Sensors 2020, 20(6), 1709; https://doi.org/10.3390/s20061709 - 19 Mar 2020

Cited by 7 | Viewed by 3711

Abstract

In collective sports, reactive agility training methodologies allow to evaluate and improve the player performance, being able to consider a mixture of technical, tactical, physical, and psychological abilities, similarly to real game-play situations. In this article, we present a new methodology for reactive agility training (neural training), the technological setup for the methodology, and a new footstep tracking algorithm, as the key element for automating the speed data gathering process, necessary for obtaining the relevant variables of the neural training approach. This new methodology is oriented to accurately measure two of the most relevant variables for reactive agility training: total response time (sprint time) and response correctness, related to a stimuli sequence presented to a player. The stimuli were designed to properly represent realistic competitive conditions for player training, contextualized to soccer. In order to automate the gathering process, a new computer vision based automatic footstep detection algorithm has been integrated to the system. The algorithm combines Kalman Filters, segmentation techniques, and perspective geometry, for obtaining highly precise detections of the moment a relevant footstep occurs in real-time, reaching a precision higher than 97%. Plus, the algorithm does not require any special marker, invasive sensor, or clothing constraint on the player. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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16 pages, 1528 KiB

Open AccessArticle

Effects of Whole-Body Electromyostimulation on Physical Fitness in Postmenopausal Women: A Randomized Controlled Trial

by Alvaro Pano-Rodriguez, Jose Vicente Beltran-Garrido, Vicenç Hernandez-Gonzalez and Joaquín Reverter-Masia

Sensors 2020, 20(5), 1482; https://doi.org/10.3390/s20051482 - 08 Mar 2020

Cited by 13 | Viewed by 3837

Abstract

Whole-body electromyostiulation (WB-EMS) has experienced a boom in recent years, even though its effectiveness is controversial. A sedentary lifestyle is deeply rooted in the European population, mainly in the elderly. This experimental study analyzed the impact of WB-EMS on the physical fitness of postmenopausal women. Thirty-four healthy sedentary women between 55 and 69 years followed an experimental design pre–post-test. Both groups conducted a ten-week aerobic and strength training program. The experimental group overlaid the WB-EMS during exercise. At the end of the intervention, both groups improved upper and lower body strength, lower extremity flexibility, agility, and speed levels (p_Bonferroni < 0.05). Significant interactions were observed at upper and lower body strength, agility, speed, and cardiovascular endurance (p < 0.05). The WB-EMS group scored better agility than the control group at the end of the intervention (p_Bonferroni < 0.05) and was the only group that improved cardiovascular endurance. WB-EMS shows a favorable isolate effect on the development of dynamic leg strength, agility, and cardiovascular endurance but did not in dynamic arm strength, gait speed, balance, or flexibility of postmenopausal women. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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8 pages, 255 KiB

Open AccessArticle

Muscle Activation in Middle-Distance Athletes with Compression Stockings

by Diego Moreno-Pérez, Pedro J. Marín, Álvaro López-Samanes, Roberto Cejuela-Anta and Jonathan Esteve-Lanao

Sensors 2020, 20(5), 1268; https://doi.org/10.3390/s20051268 - 26 Feb 2020

Cited by 4 | Viewed by 3244

Abstract

The aim of this study was to evaluate changes in electromyographic activity with the use of gradual compression stockings (GCSs) on middle-distance endurance athletes’ performance, based on surface electromyography measurement techniques. Sixteen well-trained athletes were recruited (mean ± SD: age 33.4 ± 6.3 years, VO_2max 63.7 ± 6.3 mL·kg⁻¹·min⁻¹, maximal aerobic speed 19.7 ± 1.5 km·h). The athletes were divided into two groups and were assigned in a randomized order to their respective groups according to their experience with the use of GCSs. Initially, a maximum oxygen consumption (VO_2max) test was performed to standardize the athletes’ running speeds for subsequent tests. Afterward, electromyographic activity, metabolic, and performance variables for each group were measured with surface electromyography. In addition, blood lactate concentration was measured, both with and without GCSs, during 10 min at 3% above VT2 (second ventilatory threshold), all of which were performed on the track. Next, surface electromyography activity was measured during a 1 km run at maximum speed. No significant changes were found in electromyography activity, metabolic and performance variables with GCSs use (p > 0.164) in any of the variables measured. Overall, there were no performance benefits when using compression garments against a control condition. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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11 pages, 1922 KiB

Open AccessLetter

Breath Acetone Measurement-Based Prediction of Exercise-Induced Energy and Substrate Expenditure

by Min Jae Kim, Sung Hyun Hong, Wonhee Cho, Dong-Hyuk Park, Eun-Byeol Lee, Yoonkyung Song, Yong-Sahm Choe, Jun Ho Lee, Yeonji Jang, Wooyoung Lee and Justin Y. Jeon

Sensors 2020, 20(23), 6878; https://doi.org/10.3390/s20236878 - 01 Dec 2020

Cited by 3 | Viewed by 3368

Abstract

The purpose of our study was to validate a newly developed breath acetone (BrAce) analyzer, and to explore if BrAce could predict aerobic exercise-related substrate use. Six healthy men ran on a treadmill at 70% of maximal oxygen consumption (VO_2max) for 1 h after two days of a low-carbohydrate diet. BrAce and blood ketone (acetoacetate (ACAC), beta-hydroxybutyrate (BOHB)) levels were measured at baseline and at different time points of post-exercise. BrAce values were validated against blood ketones and respiratory exchange ratio (RER). Our results showed that BrAce was moderately correlated with BOHB (r = 0.68, p < 0.01), ACAC (r = 0.37, p < 0.01) and blood ketone (r = 0.60, p < 0.01), suggesting that BrAce reflect blood ketone levels, which increase when fat is oxidized. Furthermore, BrAce also negatively correlated with RER (r = 0.67, p < 0.01). In our multiple regression analyses, we found that when BMI and VO_2max were added to the prediction model in addition to BrAce, R² values increased up to 0.972 at rest and 0.917 at 1 h after exercise. In conclusion, BrAce level measurements of our BrAce analyzer reflect blood ketone levels and the device could potentially predict fat oxidation. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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10 pages, 6898 KiB

Open AccessLetter

Verification and Evaluation of a Visual Reaction System for Badminton Training

by Kuei-Pin Kuo, Hsun-Heng Tsai, Ching-Yi Lin and Wei-Te Wu

Sensors 2020, 20(23), 6808; https://doi.org/10.3390/s20236808 - 28 Nov 2020

Cited by 8 | Viewed by 5616

Abstract

The two aims of this study were (1) designing and developing an affordable visual reaction system for badminton training that monitors and provides instant feedback on agility; and (2) to measure and improve the footwork and movement of badminton players and output useful reference data. Ten junior high school badminton players were invited to serve as the subjects of this study. They participated in a three-week (nine sessions) training program. Training was primarily in the form of fixed or random footwork drills. Timed tests were performed before and after each session to measure the players’ agility in performing six-point and four-point footwork drills. The results were compared to the training effects calculated using dependent-sample t-tests. In addition, the long-term durability and functionality of the training system were tested. The training system was able to maintain stable and reliable training and evaluation operations for extended periods. Results showed significant improvements in the visual reaction time (p = 0.003) and agility (p = 0.001) of players. The proposed training system is an affordable option for training and monitoring, evaluating, and recording training performance. It can accurately record movement and response times and simulate competitive environments. Full article

(This article belongs to the Special Issue Sensors for Exercise and Sport Activities: From Health Promotion to Sports Performance)

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