https://jast.uma.ac.ir/ Journal of Advanced Sport Technology en daily 1 Fri, 01 May 2026 00:00:00 +0330 Fri, 01 May 2026 00:00:00 +0330 https://jast.uma.ac.ir/article_4210.html Background: The present study aimed to examine the effectiveness of a virtual reality intervention in enhancing self-efficacy and intrinsic motivation among adolescent Football players.Methods: A quasi-experimental design with pretest–posttest and control group was employed. Twenty-four male football players (aged 13–18) were randomly assigned to either the experimental (VR) group or the control group (n = 12 per group). The VR intervention, based on the Nintendo Wii Fit platform, spanned eight weeks and included 24 sessions. Self-efficacy was assessed using the Sports Self-Efficacy Scale, and intrinsic motivation was measured with a localized version of the Self-Regulation Questionnaire. Data were analyzed using two-way repeated-measures ANOVA.Results: Statistically significant improvements were observed in both self-efficacy (P = 0.003) and intrinsic motivation (P = 0.010) in the experimental group. A significant time × group interaction effect was found for intrinsic motivation (P = 0.001), with post-test scores in the VR group 17.51% higher than those of the control group.Conclusions: The findings provide empirical validation for VR as a psychologically beneficial training modality in adolescent sport contexts. By fulfilling key psychological needs related to competence, autonomy, and engagement, VR can enhance motivational dynamics and perceived self-regulation in youth athletes. These results suggest that VR-based interventions, when grounded in psychological theory, offer a promising supplementary strategy for coaches, physical educators, and sport psychologists aiming to foster long-term psychological readiness and participation among adolescent athletes. https://jast.uma.ac.ir/article_4252.html Walking, as a complex motor activity, requires precise coordination within the neuromuscular system. This study aimed to analyze the multiscale complexity of electroencephalography (EEG) signals and kinematic data during walking to investigate brain-lower limb interactions. Thirteen male participants walked on a treadmill under controlled conditions, during which EEG signals and kinematic data were recorded. Multifractal complexity analysis using the multifractal detrended fluctuation analysis (MF-DFA) method was applied to the data to extract the Hurst exponent as a complexity index for dynamic features of movements in displacement dimensions along three axes (X, Y, Z) and cortical activity in motor brain regions (C3 and C4) during walking. Results indicated that the generalized Hurst exponent H(q) in the C3 and C4 regions was similar and exhibited a significant positive correlation with the same parameter in the dynamics of the contralateral limb, supporting the principle of interhemispheric control. Segmental analysis of the thigh, shank, and foot revealed substantial dynamic symmetry between the right and left sides. The multifractal patterns of the segments demonstrated significant differences, with the highest H(q) in the shank and the lowest in the thigh. Strong intra-system coordination among segments suggests an integrated organization in motor control. These findings confirm neuromuscular symmetry and coordination, provide utility for assessing motor disorders and designing rehabilitation protocols, and underscore the importance of multiscale analysis in elucidating complex brain-body interactions, with potential applications in neuroscience, biomechanics, and rehabilitation research. https://jast.uma.ac.ir/article_4255.html Introduction: With the advancement of technology in the sports industry, achieving economic sustainability in key processes such as ticketing remains a significant challenge. Digital technologies, including electronic ticketing and blockchain, offer opportunities to enhance transparency, reduce costs, and improve efficiency. However, user adoption and technical complexities pose barriers to realizing these benefits.Objectives: This study aims to investigate the simultaneous role of technology acceptance factors and blockchain capabilities in achieving economic sustainability within the context of digital ticketing in the Iranian Premier Football League.Material and Methods: The study population comprised managers and experts associated with the Iranian Premier Football League, selected through purposive and convenience sampling (N=184). Data were collected using standardized questionnaires on technology acceptance factors, blockchain capabilities, and economic sustainability. The validity of the questionnaires was confirmed by eight sports management professors, and reliability was assessed using Cronbach’s alpha and composite reliability. Descriptive statistics were analyzed using SPSS version 27, and structural equation modeling was performed with Smart PLS version 3.2.Results: The results indicated that adoption intention for digital ticketing had a positive and significant effect on economic sustainability (β=0.209, t=2.726). Blockchain capabilities positively and significantly influenced both adoption intention for digital ticketing (β=0.186, t=2.771) and economic sustainability (β=0.574, t=8.369). Complexity positively affected perceived ease of use (β=0.616, t=12.265). Extrinsic motivation and perceived usefulness significantly influenced adoption intention for digital ticketing (β=0.351, t=5.748; β=0.369, t=5.352). However, perceived ease of use had no significant effect on adoption intention (β=0.05, t=0.649, p=0.517). Relative advantage significantly impacted perceived usefulness (β=0.565, t=10.573).Discussion and Conclusion: The findings highlight that successful implementation of innovative technologies like blockchain in the sports industry requires addressing both technical aspects and user perceptions. Blockchain capabilities and technology acceptance factors are critical drivers of economic sustainability in digital ticketing. Future strategies should focus on enhancing user motivation and simplifying technology use to maximize adoption and sustainability. https://jast.uma.ac.ir/article_4604.html Background: The loss of upper limb functionality severely impacts daily living and mobility, driving the need for advanced prosthetic and rehabilitative solutions. Soft robotics has emerged as a promising alternative to rigid systems, offering inherent safety, adaptability, and intuitive control. This review synthesizes recent advancements (2021–2025) in soft robotic applications for hand rehabilitation and sports biomechanics, highlighting their potential to restore dexterity and enhance performance.Methods: A systematic literature review was conducted following PRISMA guidelines, screening 147 articles from Google Scholar, PubMed, Scopus, and WOS. Eleven studies met the inclusion criteria, focusing on soft robotic hands, assistive gloves, and wearable devices for rehabilitation and sports. Data were analyzed for design innovations, control mechanisms, clinical efficacy, and user outcomes.Results: Key advancements include: (1) multi-DOF prosthetic hands (e.g., 14-DOF design with 87.3% gesture recognition accuracy), (2) Tendon-driven assistive gloves (20–80N grasp force; 4.53/5 user satisfaction), and (3) Wearable training devices (75% improvement in motor skill retention). Soft robotics outperformed rigid systems in adaptability and user experience but faced limitations in power efficiency and durability. Machine learning-enhanced control (e.g., ProMP algorithms) and EMG feedback improved intuitive interaction.Conclusions: Soft robotics demonstrates transformative potential in rehabilitation and sports, though challenges in scalability and clinical validation persist. Future research must prioritize biomimetic refinement, energy-efficient actuation, and large-scale trials to transition prototypes into real-world solutions. Interdisciplinary collaboration will be critical to advancing this field and improving quality of life for users globally. https://jast.uma.ac.ir/article_4620.html Background: This study examined three fundamental questions: what roles artificial intelligence play in physical education, what are the risks associated with the utilization of artificial intelligence, and what strategies should be implemented to ensure the effective use of artificial intelligence in physical education?Methods: Three groups of participants took part in the research: group 1 included 1-10 specialists who served as presenters on 4 expert panels on artificial intelligence and education, group 2 included 2-7 experts in physical education, and group 3 included 3-4 experts in artificial intelligence. The data was gathered by recording the statements of experts in the specialized panels and interviewing the other experts involved. Thematic analysis was utilized to examine the data. The initial coding process occurred after the four expert panels and then after each interview. Two methods were employed to ensure reliability: 1) the conceptual network extracted from the interview text was given to the interviewees for their review and approval, and 2) the method of using critical friends was utilized. Results: The first theme identified explored the functions of artificial intelligence, including standardization of space and sports equipment, empowerment and professional development of PE teachers, classroom management, educational planning, improving assessment processes, and the production of PE content. The second theme included threats such as depriving students of thinking and creativity, emotional and social damages, scientific credibility of the presented content, and ethical concerns. Finally, the third theme indicated six basic strategies for the optimal use of artificial intelligence: 1) preventative and deterrent policies to limit any negatives of AI, 2) understanding problems and challenges that AI can address, 3) developing AI literacy among teachers, 4) promoting AI among teachers to maximise its benefits, 5) provision of the necessary infrastructure for the use of AI, and 6) ensuring the safety and security of users.Conclusions: In practice, the findings highlighted the future uses of AI within physical education, along with the potential negatives of AI that need to be carefully managed. PE teachers should be encouraged to increase their AI knowledge and skills, so that they can implement AI within their practices. https://jast.uma.ac.ir/article_4651.html The aim of this study was to identify the advantages and disadvantages of implementing artificial intelligence in sports events. The research followed a mixed research design, specifically a sequential exploratory approach, beginning with qualitative research and then transitioning to quantitative research. Data for the study were collected in the field. Study's population consisted of two parts: qualitative and quantitative. For the qualitative section, 15 experts in sports management were interviewed. In the quantitative section, the population included sports management elites, such as faculty members from physical education universities under the Ministry of Science, as well as managers and executive experts in the country's sports industry. The sample for this section was selected using a stratified-random sampling method. To analyze the data and determine the advantages and disadvantages of using artificial intelligence in sports events, the Delphi method was employed in three stages. The result of this process was a questionnaire consisting of 45 indicators across 11 components for the advantages section, and 12 indicators across 4 components for the disadvantages section. The questionnaire was compiled using a Likert scale. The face and content validity of the questionnaire were confirmed by 15 experts, and its reliability was assessed in a preliminary study involving 30 participants, yielding a value of 0.82. Additionally, exploratory factor analysis was conducted using SPSS software to analyze the data. Based on the research findings, the main advantages of using artificial intelligence in sports events were identified as refereeing, recruitment and selection of technical staff and players, analysis of player performance and information, and news agencies. On the other hand, the main disadvantages were found to be high cost, lack of human interaction between coaches and athletes, and dependence on artificial intelligence. https://jast.uma.ac.ir/article_3704.html Introduction: It is very important to pay attention to the physical and mental health of professional athletes. Transcranial direct current stimulation (tDCS) as a new method might be useful to reach this goal. Objectives: This study aims to investigate the effects of chronic effects of tDCS technology on performance, body composition, depression, anxiety and stress of professional swimmers. Materials and Methods: 19 male professional swimmers (age: 19.00±2.86 years) participated in the present study. On the first day, body composition, depression, anxiety and stress of athletes were evaluated. On the second day, swimming test was performed; according their pre-test records, participants were randomly divided into tDCS (n=10) and sham (n=9) groups. From the next day, 10 sessions of tDCS on the left hemisphere were applied three days a week. Two days after the last stimulation session, the initial evaluations were repeated. Statistical analysis was done with ANCOVA method. Results: Swimming time records decreased significantly. The stress scores decreased significantly but no significant change was observed in none of the body composition variables (weight, body mass index, total body fat and total body skeletal muscle). Also, there was no significant change in depression and anxiety scores. Discussion: According to the results of the present study, it seems that 10 sessions of tDCS along with the professional swimmers training, improves swimming performance and reduces the stress. Conclusion: According to the results of the present research, use of tDCS as a helpful technology to improve athletes’ performance and developing their psychological aspects is recommended. https://jast.uma.ac.ir/article_4079.html The DRS (Drag Reduction System) in Formula 1 races is recognized as a key technology for improving vehicle performance and enhancing competitiveness. This system reduces air resistance in specific sections of the track, enabling higher speeds and shorter lap times. The aim of this study is to examine the impacts of DRS on vehicle performance under different track conditions, analyze lap times, and assess its effects on overtaking strategies. Using advanced statistical tools such as R, Python, and SPSS, recent Formula 1 race data were analyzed to extract patterns and relationships between DRS usage and lap times. The results showed that activating DRS, especially on long straights, significantly reduced lap times and increased vehicle speed. Additionally, the study revealed that the effects of DRS varied under different weather conditions and track types, with the technology being less impactful in certain circumstances. Overall, optimal use of DRS can assist drivers in overtaking and shifting competitive positions during tight races. This research emphasizes the importance of statistical analyses and simulation models for designing successful strategies in Formula 1 races. https://jast.uma.ac.ir/article_4523.html This study examines the primary factors influencing media transformation and artificial intelligence (AI), with a particular emphasis on identifying critical challenges and opportunities within the sports sector. Media transformation in the age of AI is not merely the outcome of technological advancements; rather, it results from a complex interplay of economic, social, cultural, and legal forces that shape its future trajectory in a nonlinear and multi-scenario manner. Accordingly, this research adopts a foresight methodology by integrating Delphi-based cross-impact analysis with MICMAC structural analysis to identify key drivers across political, economic, social, technological, environmental, and legal (PESTEL) dimensions. In terms of purpose, this study is applied-developmental, and methodologically, it employs a mixed-methods (qualitative–quantitative) approach. In the first stage, a set of factors influencing AI-driven transformation in the media industry was identified through environmental scanning and a systematic review of the scientific literature. These factors were subsequently refined through three rounds of Delphi with the participation of experts in media, communication, and information technology, resulting in a final consensus on 18 key drivers. In the next stage, structural analysis using MICMAC software was conducted to examine the interrelationships among these drivers. The results of direct and indirect influence analysis revealed that variables such as the concentration of capital and market power in AI-driven media platforms, the orientation of public policy and regulation, data and algorithmic infrastructures, and the level of technological autonomy constitute the most influential and determining system variables. In contrast, variables such as legal requirements for algorithmic transparency, public trust in AI-generated content, and the professional skills of the media workforce were identified as dependent variables. Focusing on the sports industry as one of the most significant sectors within the media landscape, the findings highlight strategic opportunities for the development of sports media and provide actionable insights for managers seeking to leverage AI-driven transformations. https://jast.uma.ac.ir/article_4526.html This systematic review investigated the role of artificial intelligence (AI) in professional weightlifting in recent years. With the increasing advancement of technology, artificial intelligence has become one of the important tools in all sciences, especially in the field of sports science. AI's significance was observed across various domains, including biomechanical movement analysis, performance prediction, training program optimization, and injury risk mitigation. Findings indicate that machine learning and computer vision algorithms can accurately identify weightlifters' movement patterns and detect technical errors with superior precision compared to human observers. Moreover, data-driven predictive models demonstrate effectiveness in adjusting training loads, monitoring fatigue, and delivering personalized recommendations.Despite these advancements, challenges persist, such as the scarcity of large, standardized datasets, the lack of established motion capture protocols, and limitations in generalizing models across elite athletes. A notable gap exists in field research, with most existing studies confined to laboratory settings, highlighting the need for testing AI models under real-world training and competition conditions.This systematic review concludes that AI serves as a potent tool for enhancing performance and reducing injury risk in national and professional weightlifting. However, realizing AI's full potential necessitates improvements in data infrastructure, enhanced collaboration between AI specialists, sports coaches, and athletes, and further research. Future developments are poised to enable the implementation of sophisticated intelligent systems for coaches and athletes. https://jast.uma.ac.ir/article_4616.html Introduction: This study aimed to analyze the structural relationship between Iranian volleyball fans’ satisfaction with the Video Assistant Referee (VAR) system and their social identity, considering the mediating roles of analytical enjoyment and attitude toward technology in decision-making. The statistical population comprised volleyball fans attending matches of the Iranian Premier Volleyball League in 2023. Methods: Using a convenience sampling method, a total of 384 fans participated in the study. Data were collected using standardized questionnaires on fan satisfaction with VAR, social identity, analytical enjoyment, and attitude toward technology. Descriptive and inferential statistical analyses, including the Kolmogorov–Smirnov test and structural equation modeling (SEM), were applied. Results: The results indicated a positive and significant relationship between fan satisfaction with VAR and social identity through the mediating role of attitude toward technology. Conclusion: Since this type of performance has made this type of system an important component of the game, and sports fans feel good about it and consider it one of the most important elements in the process of holding a match, this sense of identity towards the technology has led to its emergence and further expansion in the sports industry Also, study found that fans' sense of close identification with their team is enhanced by decision-aiding technology, as it limits opportunities to discuss why their team may have been unfairly treated in certain match situations. Video referee assistance helps support accurate decisions by reducing controversial elements in the game of volleyball, which improves and changes fan perceptions of match refereeing https://jast.uma.ac.ir/article_4670.html IntroductionPolarized training is recognized as an effective model for improving endurance performance. However, accurate determination of aerobic and anaerobic thresholds remains challenging because conventional methods such as cardiopulmonary exercise testing or blood lactate measurement have technical and practical limitations.BackgroundThis study aimed to design and validate an algorithm based on the Short Distance Maximum (S.Dmax) method to estimate metabolic thresholds and to provide individualized polarized training prescriptions.MethodsThis applied-developmental study was conducted with 30 elite football players from the Iranian national deaf team. Heart rate data were recorded during a progressive treadmill test to exhaustion using a Polar device, and heart rate performance curves (HRPC) were plotted. Aerobic and anaerobic thresholds were calculated using the Narita equation and the Dmax method. Subsequently, a dedicated software was developed to automatically identify thresholds, determine training ranges, and generate polarized training prescriptions with a 3:1 low- to high-intensity ratio.ResultsIndependent t-test analysis indicated no statistically significant differences (p > 0.05) between training ranges determined by the developed software and the standard Dmax method. The software successfully extracted accurate thresholds and provided individualized polarized training prescriptions.DiscussionThe findings suggest that the proposed S.Dmax-based algorithm can reliably determine metabolic thresholds without the need for invasive procedures. By offering accurate and individualized training zones, this method supports the practical application of polarized training in professional sports settings.ConclusionThe developed S.Dmax-based algorithm and software proved to be a valid, reliable, and non-invasive tool for determining metabolic thresholds and prescribing polarized training. This approach provides a cost-effective alternative to laboratory methods and can be applied effectively in sports, research, and educational contexts. https://jast.uma.ac.ir/article_4765.html Introduction and objectives: Wearable inertial measurement units (IMUs) can objectively assess children's motor competence, yet their raw outputs remain inaccessible to non expert users such as teachers and coaches. The Swain et al.’s (2024) framework specifies three feedback themes—"Grab and Go", "Adjust and Adapt", and "Visualize and Feedback"—that are essential for user centred systems. However, the extent to which existing IMU based studies have addressed these dimensions is unknown. This systematic review aims to determine the extent to which existing IMU based studies have addressed these feedback dimensions and to propose an evidence informed framework for designing user centred feedback systems for teachers and coaches. Materials and Methods: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines. Three databases (Web of Science, IEEE, and Scopus) were searched up to February 2025. Studies were included if they used IMUs to assess fundamental movement skills in children (4–12 years) and reported quantitative outcomes. Methodological quality was assessed using the JBI checklist. Each study was mapped against the 14 sub dimensions of the Swain framework and was classified as Type I (neglect: no feedback) or Type II (poor performance: feedback attempted but inadequate for non experts). Results: Twenty three studies were included. Nineteen (83%) were Type I —no feedback was provided. Four (17%) were Type II —feedback was limited to raw numbers (e.g., jump height) or graphs requiring expert interpretation. No study addressed personalisation (A1–A3), multimodal feedback (V2–V4), or referral alerts (R1–R2). Six persistent gaps were identified: Lack of actionable feedback, personalisation, multimodality, avatar based visualisation, referral mechanisms, and emotional engagement. Discussion and Conclusions: IMU based motor assessment has prioritised measurement accuracy while systematically neglecting the feedback needs of teachers and coaches. A seven step evidence informed framework is proposed, including hardware simplification (≤3 IMUs), developmental level personalisation, stepwise multimodal feedback, teacher referral alerts, field validation in schools, and open science practices. Closing the feedback gap requires a cultural shift from engineer centred validation to a teacher centred design. https://jast.uma.ac.ir/article_4766.html This research focuses on the Manufacturing of a static and dynamic fencing device capable of evaluating and improving hit accuracy and speed under psychologically loaded and unloaded conditions. This device has the capability to provide visual and auditory stimuli, and estimate the amount of force applied. Additionally, a training partner is placed on installed rails, which has both static and dynamic capabilities and can move. To simulate a competition state, the memory in the training partner provides general and detailed information, including error percentage, performance speed in the same session or in comparison to previous sessions. Stimuli are provided in three modes: simple, selective, and differential, to increase decision-making speed through training and coordination. The use of a loudspeaker to play spectator sounds and the provision of colored stimuli at the moment with psychological load and without them at the moment without cognitive load is done to standardize the training partner's conditions with the opponent's training state in a competition. This device can be adjusted by the coach or by the athlete themselves, with or without the coach's presence. The final report of the completed training is available both in print and display. Ultimately, based on the obtained information, the coach can make changes to their training and exercises if necessary. https://jast.uma.ac.ir/article_4767.html The rapid advancement of technology in recent decades has provided countless opportunities for using new tools and systems in the sports industry and the organization of sports events. The research was conducted to identify the challenges of using new technologies in holding sporting events. The study was conducted in two sequential exploratory mixed methods stages. In the qualitative section, thematic analysis was used; in the quantitative area, PLS 3.0 software was used to analyze the data. The study population consisted of technology experts, management experts, and scholars. In the qualitative section, purposeful snowball sampling was used to select sample members for in-depth interviews. In total, 15 interviews were conducted. In the quantitative area, the sample size was considered 250 people. The results showed that the most important challenges include A) financial and infrastructure challenges, B) human resource challenges, C) legal and security challenges, and D) user-related challenges. Overall, the findings highlight the multifaceted nature of the challenges of using new technologies in holding sporting events, with financial, human resource, legal, and user-based factors presenting significant barriers. Targeted investments, strategic partnerships, updated policies, and user-centric design approaches are recommended to address these interrelated challenges holistically. https://jast.uma.ac.ir/article_4784.html Background: Anterior cruciate ligament (ACL) rupture is among the most common lower-limb injuries, often causing persistent alterations in biomechanics and increasing the risk of early-onset osteoarthritis. Biomechanical tools such as foot-scan and force plate systems provide valuable insights by accurately measuring plantar pressure distribution, center of pressure trajectories, and ground reaction forces. This systematic review aimed to examine the role of these devices in predicting risk factors and assessing biomechanical changes in ACL-injured and reconstructed patients. Methods: A comprehensive search was conducted across international databases (PubMed, Scopus, Web of Science) and national databases (SID, Magiran, Noormags) for studies published from January 2000 to January 2025, ensuring coverage of all relevant literature in this period. After screening according to eligibility criteria and quality assessment with the McMaster tool, 11 studies were included. Given the heterogeneity of study designs and outcomes, a narrative synthesis was applied. Results: The reviewed studies showed that ACL patients, even after rehabilitation, exhibited persistent abnormalities in plantar pressure patterns, center of pressure trajectories, and ground reaction forces. These deficits were more pronounced in dynamic tasks such as jumping and running. Neuromuscular training interventions improved some loading patterns and reduced risk factors, though biomechanical assessments still revealed residual deficits. Conclusions: Foot-scan and force plate devices are sensitive indicators for identifying biomechanical abnormalities and predicting secondary injuries in ACL patients. Their integration into multidimensional rehabilitation programs, such as return-to-sport screening, prescription of orthoses, or targeted neuromuscular training, may enhance clinical decision-making, facilitate safer return to sports, and help prevent early-onset osteoarthritis. However, small sample sizes and methodological heterogeneity among included studies represent limitations that should be considered when interpreting findings. https://jast.uma.ac.ir/article_4812.html Introduction and Objective: Considering the importance of assessing synergies and patterns of single-joint and biarticular muscles during walking for improving the diagnosis and management of orthopedic and neurological conditions, this study aimed to compare the performance of single-joint and biarticular muscle synergies with outputs from AnyBody and OpenSim during walking. Methodology: In this study, kinetic, kinematic, and electromyography (EMG) data of the lower limb were collected from 32 participants during self-selected speed walking. Kinetic and kinematic data processed through AnyBody and OpenSim software were compared with normalized EMG data using the SPM method. Additionally, the temporal EMG correlation matrix was utilized to analyze synergist muscles. Results: SPM analysis indicated good agreement between normalized EMG data and the outputs from AnyBody and OpenSim software. However, during certain phases of the gait cycle, normalized EMG values reached higher peaks (p < 0.05). The temporal EMG correlation matrix during walking revealed the following: • Quadriceps muscles showed strong correlations (above 0.92) during knee extension. • Hamstrings exhibited moderate to strong correlations (0.67) during knee flexion and hip extension. • Calf muscles demonstrated strong correlations (above 0.94) during ankle plantarflexion. • Gluteus medius and tensor fasciae latae showed strong correlations (0.9) during hip abduction and pelvic stabilization. Conclusion: The results indicated that AnyBody was more accurate in estimating single-joint muscle activity, while OpenSim performed better in analyzing biarticular muscles and more complex movement patterns. These findings could contribute to improving simulation models and developing new strategies for diagnosing and treating movement disorders.