Digital Technologies: Applications, Window of Opportunity and Challenges in Exercise, Health and Sports

A special issue of Sports (ISSN 2075-4663).

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 39308

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Guest Editor
1. Research Center in Physical Activity, Health and Leisure (CIAFEL), Faculty of Sports, University of Porto (FADEUP), 4099-002 Porto, Portugal
2. Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
Interests: exercise; health; sports training; training process; training periodization; training and detraining; exercise and sport physiology; energetics; bioenergetics; human locomotion; pulmonary function; oxygen uptake kinetics; biomarkers; thermal physiology; electrochemical biosensors; microneedle biosensors; strength and conditioning; exercise and sport biomechanics; digital technologies; wearable technologies; smart textiles; physical fitness assessment; elite athletes; training and testing; physical activity monitoring; performance analysis
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Aquatic Sports Research Group, School of Physical Education, Physiotherapy, and Dance; Federal University of Rio Grande do Sul, Porto Alegre 90690-200, Brazil
Interests: sports; health; technology; network analysis; machine learning technique; biomechanics; swimming
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CESPU, Institute of Research and Advanced Training in Health Sciences and Technologies (IINFACTS), PRD 4585-116 Gandra, Portugal
Interests: exercise; health; artificial intelligence; data analysis; statistical modeling; programming; algorithms; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Digital technology is opening unique opportunities for exercise, health, and sports development. Experience in these areas is growing fast due to advances in digital technologies. From the use of software and wearable devices to advanced data analysis approaches, there is a great range of possibilities and improvements when using digital technologies. This Special Edition will underline new and emerging methodologies to bring innovative solutions for exercise, health and sports, including digital technologies, software development/validation, mobile applications, wearable devices, the Internet of Things, artificial intelligence, complex systems, and network analysis. Original research, case reports, and review articles from this field will be considered.

Dr. Rodrigo Zacca
Dr. Flávio Antônio de Souza Castro
Dr. Rui Miguel Simões de Azevedo
Guest Editors

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Keywords

  • digital technology
  • software
  • mobile application
  • wearable
  • internet of things
  • artificial intelligence
  • network analysis
  • exercise
  • health
  • sports

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Published Papers (11 papers)

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Editorial

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3 pages, 177 KiB  
Editorial
Riding the Digital Wave of Exercise, Health, and Sports Training Optimization
by Rodrigo Zacca, Flávio Antônio de Souza Castro and Rui M. S. Azevedo
Sports 2024, 12(8), 203; https://doi.org/10.3390/sports12080203 - 25 Jul 2024
Viewed by 924
Abstract
The digital era is opening countless possibilities in “Sport Sciences”; “Public, Environmental, and Occupational Health”; and “Physical Therapy, Sports Therapy, and Rehabilitation” areas [...] Full article

Research

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6 pages, 680 KiB  
Communication
Feasibility of Using Laser Imaging Detection and Ranging Technology for Contactless 3D Body Scanning and Anthropometric Assessment of Athletes
by Katja Oberhofer, Céline Knopfli, Basil Achermann and Silvio R. Lorenzetti
Sports 2024, 12(4), 92; https://doi.org/10.3390/sports12040092 - 26 Mar 2024
Cited by 2 | Viewed by 1592
Abstract
The scope of this pilot study was to assess the feasibility of using the laser imaging detection and ranging (LiDAR) technology for contactless 3D body scanning of sports athletes and deriving anthropometric measurements of the lower limbs using available software. An Apple iPad [...] Read more.
The scope of this pilot study was to assess the feasibility of using the laser imaging detection and ranging (LiDAR) technology for contactless 3D body scanning of sports athletes and deriving anthropometric measurements of the lower limbs using available software. An Apple iPad Pro 3rd Generation with embedded LiDAR technology in combination with the iOS application Polycam were used. The effects of stance width, clothing, background, lighting, scan distance and measurement speed were initially assessed by scanning the lower limbs of one test person multiple times. Following these tests, the lower limbs of 12 male and 10 female participants were scanned. The resulting scans of the lower limbs were complete for half of the participants and categorized as good in quality, while the other scans were either distorted or presented missing data around the shank and/or the thigh. Bland–Altman plots between the LiDAR-based and manual anthropometric measures showed good agreement, with the coefficient of determination from correlation analysis being R2 = 0.901 for thigh length and R2 = 0.830 for shank length, respectively. The outcome of this pilot study is considered promising, and a further refinement of the proposed scanning protocol and advancement of available software for 3D reconstruction are recommended to exploit the full potential of the LiDAR technology for the contactless anthropometric assessment of athletes. Full article
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12 pages, 4535 KiB  
Article
Effects of Cycling on Spine: A Case–Control Study Using a 3D Scanning Method
by Antonino Patti, Valerio Giustino, Giuseppe Messina, Flavia Figlioli, Stefania Cataldi, Luca Poli, Giacomo Belmonte, Alessandro Valenza, Alessandra Amato, Ewan Thomas, Izabela Rutkowska, Paula Esteban-García, Antonio Palma and Antonino Bianco
Sports 2023, 11(11), 227; https://doi.org/10.3390/sports11110227 - 15 Nov 2023
Cited by 1 | Viewed by 2575
Abstract
Background: Few studies have investigated the effects of adopting a specific and prolonged posture on cyclists. This study aimed to evaluate the upright spine in a sample of recreational cyclists and compare it with a sample of non-cyclists, though still athletes, through a [...] Read more.
Background: Few studies have investigated the effects of adopting a specific and prolonged posture on cyclists. This study aimed to evaluate the upright spine in a sample of recreational cyclists and compare it with a sample of non-cyclists, though still athletes, through a 3D scanning method. Methods: Forty-eight participants were enrolled in this observational study. The sample consisted of 25 cyclists for the cycling group and 23 non-cyclist athletes for the control group. The Spine3D device (Sensor Medica, Guidonia Montecelio, Rome, Italy) was used to evaluate the spine of the participants in both groups. Results: The results showed significantly greater spine inclination in the cycling group compared to the control group (p < 0.01). Furthermore, there was a significant decrease in lumbar lordosis in the cycling group compared to the control group (p < 0.01). Conclusions: This case–control study raises the possibility that the onset of lower back pain in cyclists may be due to a reduction in lumbar lordosis. Furthermore, this study demonstrated that the Spine3D device can be used in sports to monitor the spine of athletes to prevent and reduce musculoskeletal deficits. Full article
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12 pages, 1779 KiB  
Article
Artificial Intelligence Program for Predicting Wrestlers’ Sports Performances
by Roman Sergeevich Nagovitsyn, Roza Alexeevna Valeeva and Liliia Agzamovna Latypova
Sports 2023, 11(10), 196; https://doi.org/10.3390/sports11100196 - 8 Oct 2023
Cited by 1 | Viewed by 3610
Abstract
To date, there are conflicting opinions about the effectiveness of the introduction of artificial intelligence technologies in sports. In this regard, the purpose of the study was to develop and integrate an intellectual program for predicting competitive success into the process of selecting [...] Read more.
To date, there are conflicting opinions about the effectiveness of the introduction of artificial intelligence technologies in sports. In this regard, the purpose of the study was to develop and integrate an intellectual program for predicting competitive success into the process of selecting wrestlers to increase its effectiveness. The authors developed a program for predicting the sports performance of wrestlers on the basis of artificial intelligence technology. To implement the study, the individual data of Greco-Roman wrestlers (n = 72) were collected and processed on 36 comparison traits, ranked into categories according to three key areas: sports space, hereditary data and individual achievements. As a result of data processing through means of deep neural networks and machine learning algorithms, two prediction categories were identified: athletes who performed at the sport rank or the highest standard and athletes who did not achieve this standard. Control testing of the created program showed only 11% of error probability in predicting a given wrestler’s competitive performance. As for the functionality of the program in the area of classification of the features by category, the authors’ artificial intelligence program with 100% probability identified key categories of traits that reliably affect the results of the future sports performance of a young wrestler. Thus, the use of neural networks and machine learning algorithms, according to the results of the study, improves the quality of sports selection, which will allow further timely individualization and improvement of the training process of young wrestlers. Full article
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15 pages, 1318 KiB  
Article
A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study
by Lisa Noteboom, Anouk Nijs, Peter J. Beek, Frans C. T. van der Helm and Marco J. M. Hoozemans
Sports 2023, 11(9), 170; https://doi.org/10.3390/sports11090170 - 5 Sep 2023
Cited by 2 | Viewed by 2655
Abstract
Muscle overload injuries in strength training might be prevented by providing personalized feedback about muscle load during a workout. In the present study, a new muscle load feedback application, which monitors and visualizes the loading of specific muscle groups, was developed in collaboration [...] Read more.
Muscle overload injuries in strength training might be prevented by providing personalized feedback about muscle load during a workout. In the present study, a new muscle load feedback application, which monitors and visualizes the loading of specific muscle groups, was developed in collaboration with the fitness company Gymstory. The aim of the present study was to examine the effectiveness of this feedback application in managing muscle load balance, muscle load level, and muscle soreness, and to evaluate how its actual use was experienced. Thirty participants were randomly distributed into ‘control’, ‘partial feedback’, and ‘complete feedback’ groups and monitored for eight workouts using the automatic exercise tracking system of Gymstory. The control group received no feedback, while the partial feedback group received a visualization of their estimated cumulative muscle load after each exercise, and the participants in the complete feedback group received this visualization together with suggestions for the next exercise to target muscle groups that had not been loaded yet. Generalized estimation equations (GEEs) were used to compare muscle load balance and soreness, and a one-way ANOVA was used to compare user experience scores between groups. The complete feedback group showed a significantly better muscle load balance (β = −18.9; 95% CI [−29.3, −8.6]), adhered better to the load suggestion provided by the application (significant interactions), and had higher user experience scores for Attractiveness (p = 0.036), Stimulation (p = 0.031), and Novelty (p = 0.019) than the control group. No significant group differences were found for muscle soreness. Based on these results, it was concluded that personal feedback about muscle load in the form of a muscle body map in combination with exercise suggestions can effectively guide strength training practitioners towards certain load levels and more balanced cumulative muscle loads. This application has potential to be applied in strength training practice as a training tool and may help in preventing muscle overload. Full article
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12 pages, 1622 KiB  
Article
Velocity-Based Strength Training: The Validity and Personal Monitoring of Barbell Velocity with the Apple Watch
by Basil Achermann, Katja Oberhofer, Stephen J. Ferguson and Silvio R. Lorenzetti
Sports 2023, 11(7), 125; https://doi.org/10.3390/sports11070125 - 23 Jun 2023
Cited by 3 | Viewed by 5937
Abstract
Velocity-based training (VBT) is a method to monitor resistance training based on measured kinematics. Often, measurement devices are too expensive for non-professional use. The purpose of this study was to determine the accuracy and precision of the Apple Watch 7 and the Enode [...] Read more.
Velocity-based training (VBT) is a method to monitor resistance training based on measured kinematics. Often, measurement devices are too expensive for non-professional use. The purpose of this study was to determine the accuracy and precision of the Apple Watch 7 and the Enode Pro device for measuring mean, peak, and propulsive velocity during the free-weighted back squat (in comparison to Vicon as the criterion). Velocity parameters from Vicon optical motion capture and the Apple Watch were derived by processing the motion data in an automated Python workflow. For the mean velocity, the barbell-mounted Apple Watch (r = 0.971–0.979, SEE = 0.049), wrist-worn Apple Watch (r = 0.952–0.965, SEE = 0.064) and barbell-mounted Enode Pro (r = 0.959–0.971, SEE = 0.059) showed an equal level of validity. The barbell-mounted Apple Watch (Vpeak: r = 0.952–0.965, SEE = 0.092; Vprop: r = 0.973–0.981, SEE = 0.05) was found to be the most valid for assessing propulsive and peak lifting velocity. The present results on the validity of the Apple Watch are very promising, and may pave the way for the inclusion of VBT applications in mainstream consumer wearables. Full article
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11 pages, 3955 KiB  
Article
Impact of the Anatomical Accelerometer Placement on Vertical Jump Performance Characteristics
by Damjana V. Cabarkapa, Dimitrije Cabarkapa, Nicolas M. Philipp and Andrew C. Fry
Sports 2023, 11(4), 92; https://doi.org/10.3390/sports11040092 - 21 Apr 2023
Cited by 5 | Viewed by 2285
Abstract
With rapid technological development over recent years, the use of wearable athlete monitoring devices has substantially gained popularity. Thus, the purpose of the present study was to examine the impact of the anatomical placement of an accelerometer on biomechanical characteristics of countermovement vertical [...] Read more.
With rapid technological development over recent years, the use of wearable athlete monitoring devices has substantially gained popularity. Thus, the purpose of the present study was to examine the impact of the anatomical placement of an accelerometer on biomechanical characteristics of countermovement vertical jump with and without an arm swing when compared to the force plate as a criterion measure. Seventeen recreationally active individuals (ten males and seven females) volunteered to participate in the present study. Four identical accelerometers sampling at 100 Hz were placed at the following anatomical locations: upper-back (UB), chest (CH), abdomen (AB), and hip (HP). While standing on a uni-axial force plate system sampling at 1000 Hz, each participant completed three non-sequential maximal countermovement vertical jumps with and without an arm swing. All devices recorded the data simultaneously. The following variables of interest were obtained from ground reaction force curves: peak concentric force (PCF), peak landing force (PLF), and vertical jump height (VJH). The findings of the present study reveal that the most appropriate anatomical locations to place the accelerometer device when attempting to estimate PCF, PLF, and VJH during a countermovement vertical jump with no arm swing are CH, AB, and UB, and during a countermovement vertical jump with an arm swing are UB, HP, and UB, respectively. Overall, these findings may help strength and conditioning professionals and sports scientists to select appropriate anatomical locations when using innovative accelerometer technology to monitor vertical jump performance characteristics. Full article
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14 pages, 1278 KiB  
Article
Identification of Optimal Movement Patterns for Energy Pumping
by Micha Luginbühl, Micah Gross, Silvio Lorenzetti, David Graf and Martin J. Bünner
Sports 2023, 11(2), 31; https://doi.org/10.3390/sports11020031 - 30 Jan 2023
Cited by 1 | Viewed by 2168
Abstract
Energy pumping is a way to gain kinetic energy based on an active vertical center of mass movement in rollers in sports like skateboarding, skicross, snowboard cross and BMX. While the principle of the energy transfer from the vertical movement to the horizontal [...] Read more.
Energy pumping is a way to gain kinetic energy based on an active vertical center of mass movement in rollers in sports like skateboarding, skicross, snowboard cross and BMX. While the principle of the energy transfer from the vertical movement to the horizontal movement is well understood, the question of how to achieve the optimal energy transfer is still unresolved. In this paper, we introduce an inverse pendulum model to describe the movement of the center of mass of an athlete performing energy pumping. On this basis, the problem of identifying the optimal movement pattern is formulated as an optimal control problem. We solve the discretized optimal control problem with the help of a SQP-algorithm. We uncover that the optimal movement pattern consists of a jumping, flying, and landing phase, which has to be timed precisely. We investigate how the maximal horizontal speed depends on parameters like rollers height and maximal normal force of the athlete. Additionally, we present a qualitative comparison of our results with measured results from BMX-racing. For athletes and coaches, we advice on the basis of our results that athlete’s performance is optimized by using maximal force and adopt an exact and proper timing of the movement pattern. Full article
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10 pages, 261 KiB  
Article
Effectiveness of Different Modalities of Remote Online Training in Young Healthy Males
by Michael Daveri, Andrea Fusco, Cristina Cortis and Gabriele Mascherini
Sports 2022, 10(11), 170; https://doi.org/10.3390/sports10110170 - 2 Nov 2022
Cited by 6 | Viewed by 3118
Abstract
Since 2020 there has been an increase in demand for home workouts. Therefore, different ways of delivering distance training have been proposed to promote “stay active at home.” This study aimed to compare the effectiveness of three different training programs consisting of a [...] Read more.
Since 2020 there has been an increase in demand for home workouts. Therefore, different ways of delivering distance training have been proposed to promote “stay active at home.” This study aimed to compare the effectiveness of three different training programs consisting of a total of 15 workouts (three sessions per week): supervised livestreaming (LS), unsupervised following a video recording (VR), and unsupervised following a written program (WP). Changes in anthropometric and cardiovascular variables, muscle fitness, and physical activity levels were evaluated. To provide a meaningful analysis for significant comparisons between small groups, mean differences (∆), 95% confidence interval (95% C.I.), and Cohen’s effect sizes (E.S.) were also calculated. The three training modalities increased physical activity levels, with an adherence rate of LS = 93.3%, VR = 86%, and WP = 74%. Although there was no reduction in body weight, waist circumference decreased by 1.3 cm (95% C.I. = −2.1, −0.5; E.S. = 0.170; p < 0.004). Furthermore, where LS, VR, and WP resulted in improvements in muscle fitness, only LS showed changes in cardiovascular variables, such as resting heart rate (∆ = −7.3 bpm; 95% C.I. = −11.9, −2.7; E.S. = 1.296; p < 0.001) and Ruffier’s index (∆ = −2.1bpm; 95% C.I. = −3.5, −0.8; E.S. 1.099; p < 0.001). Remote online training proved its effectiveness over a short period of time. However, supervised training proved to be the most effective, highlighting the importance of an experienced trainer. Full article
17 pages, 1335 KiB  
Article
Applicability of an Immersive Virtual Reality Exercise Training System for Office Workers during Working Hours
by Evlalia Touloudi, Mary Hassandra, Evangelos Galanis, Marios Goudas and Yannis Theodorakis
Sports 2022, 10(7), 104; https://doi.org/10.3390/sports10070104 - 29 Jun 2022
Cited by 11 | Viewed by 5343
Abstract
Virtual reality is a computer-generated simulation of a real or imaginary three-dimensional environment that has entered our lives, particularly for gaming. Lately, it has been permeating into many aspects of our everyday life, such as exercise. It is important to ascertain whether exercise [...] Read more.
Virtual reality is a computer-generated simulation of a real or imaginary three-dimensional environment that has entered our lives, particularly for gaming. Lately, it has been permeating into many aspects of our everyday life, such as exercise. It is important to ascertain whether exercise in an immersive virtual reality environment can be accepted from employees and lead to positive outcomes for them. The aim of this exploratory study was to examine the acceptance, future adoption, interest/enjoyment and usability of an immersive virtual reality system for exercise training by office workers during breaks within their working hours. A total of 40 female employees participated in the study with a mean age of 42.58 years (SD 10.77). Participants were requested to complete two sequential 15-min dual task cycling sessions corresponding to two experimental conditions. The first, condition A, involved cycling in a virtual environment, wearing a virtual reality head mounted display, and responding to cognitive tasks by answering multiple choice questions—on a screen, using a joystick. The second, condition B, involved cycling on a static bicycle and simultaneously responding to cognitive tasks by answering multiple choice questions in a real environment. After completion of the two conditions, participants responded to a series of scales regarding each of the experimental conditions and to a semi-structured interview. The results showed that participants noted a significant preference for the immersive virtual reality exercise, condition A, compared to condition B (bike only); and their acceptance, interest/enjoyment, usability and intention for future use were high. The qualitative data showed increased intention for future use, feelings of control and presence and most of the participants did not encounter any difficulties or require extra help to understand the immersive virtual reality system. Overall, exercising during working hours with an immersive virtual reality exercise system was well perceived by office workers and applicable. However, the effects of the immersive virtual reality training system on physical and mental health and the employees’ adherence to the exercise program should be tested with a longer intervention program. Full article
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Review

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13 pages, 721 KiB  
Review
The eSports Medicine: Pre-Participation Screening and Injuries Management—An Update
by Agostino Rossoni, Marco Vecchiato, Erica Brugin, Eliana Tranchita, Paolo Emilio Adami, Manuela Bartesaghi, Elena Cavarretta and Stefano Palermi
Sports 2023, 11(2), 34; https://doi.org/10.3390/sports11020034 - 1 Feb 2023
Cited by 18 | Viewed by 6759
Abstract
Recently, electronic sports (eSports) became one of the growing forms of new media due to the wide diffusion of games and online technologies. Even if there is still a debate about the definition and characterization of eSports, eAthletes train heavily, compete in tournaments, [...] Read more.
Recently, electronic sports (eSports) became one of the growing forms of new media due to the wide diffusion of games and online technologies. Even if there is still a debate about the definition and characterization of eSports, eAthletes train heavily, compete in tournaments, must abide by competition, association, and governing body rules, just like all other athletes. Furthermore, as in any other competitive discipline, there can be injuries. Aberrant sitting posture, repetitive movements, screen vision, prolonged playing hours, and a sedentary lifestyle can lead to several medical hazards in musculoskeletal, ophthalmology, neurological, and metabolic systems. Moreover, several cardiovascular changes occur in eAthletes. This paper aims to explore the different injuries that can occur in a professional eAthlete, suggesting how every high-level gamer could benefit from a pre-participation evaluation and a correct injury prevention strategy. Full article
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