Search Results (462)

Background/Objectives: Sprinting is a fundamental locomotor skill and a key indicator of lower limb strength and anaerobic power in early childhood. The aim of the study was to examine possible differences in the step kinematic parameters and their contribution to sprint speed between children with different patterns of speed development. Methods: 65 prepubescent male and female track athletes (33 males and 32 females; 6.9 ± 0.8 years old) were examined in a maximal 15 m short sprint running test, where photocells measured time for each 5 m segment. At the last 5 m segment, step length, frequency, and velocity were evaluated via a video analysis method. The symmetry angle was calculated for the examined step kinematic parameters. Results: Based on the speed at the final 5 m segment of the test, two groups were identified, the maximum sprint phase (MAX) and the acceleration phase (ACC) group. Speed was significantly (p < 0.05) higher in ACC in the final 5 m segment, while there was a significant (p < 0.05) interrelationship between step length and frequency in ACC but not in MAX. No other differences were observed. Conclusions: The difference observed in the interrelationship between speed and step kinematic parameters between ACC and MAX highlights the importance of identifying the speed development pattern to apply individualized training stimuli for the optimization of training that can lead to better conditioning and wellbeing of children involved in sports with requirements for short-sprint actions. Full article

Accurate estimation of upper-limb joint angles is essential in biomechanics, rehabilitation, and wearable robotics. While inertial measurement units (IMUs) offer portability and flexibility, systems requiring multiple inertial sensors can be intrusive and complex to deploy. In contrast, optical motion capture (MoCap) systems provide precise tracking but are constrained to controlled laboratory environments. This study presents a deep learning-based approach for estimating shoulder and elbow joint angles using only three IMU sensors positioned on the chest and both wrists, validated against reference angles obtained from a MoCap system. The input data includes Euler angles, accelerometer, and gyroscope data, synchronized and segmented into sliding windows. Two recurrent neural network architectures, Convolutional Neural Network with Long-short Term Memory (CNN-LSTM) and Bidirectional LSTM (BLSTM), were trained and evaluated using identical conditions. The CNN component enabled the LSTM to extract spatial features that enhance sequential pattern learning, improving angle reconstruction. Both models achieved accurate estimation performance: CNN-LSTM yielded lower Mean Absolute Error (MAE) in smooth trajectories, while BLSTM provided smoother predictions but underestimated some peak movements, especially in the primary axes of rotation. These findings support the development of scalable, deep learning-based wearable systems and contribute to future applications in clinical assessment, sports performance analysis, and human motion research. Full article

Rowing is a cyclic sport that consists of repetitive biomechanical actions, with performance being influenced by the balance between propulsive and resistive forces. The current study aimed to assess the relationships between intracycle velocity variation (IVV) and key biomechanical and performance variables in male and female single scullers. Twenty-three experienced rowers (10 females) completed a 2000 m rowing competition, during which boat position and velocity were measured using a 15 Hz GPS, while cycle rate was derived from the integrated triaxial accelerometer sampling at 100 Hz. From these data, it was possible to calculate distance per cycle, IVV, the coefficient of velocity variation (CVV), and technical index values. Males presented higher mean, maximum and minimum velocity, distance per cycle, CVV, and technical index values than females (15.40 ± 0.81 vs. 13.36 ± 0.88 km/h, d = 0.84; 21.39 ± 1.68 vs. 18.77 ± 1.52 km/h, d = 1.61; 11.15 ± 1.81 vs. 9.03 ± 0.85 km/h, d = 1.45; 7.68 ± 0.32 vs. 6.89 ± 0.97 m, d = 0.69; 14.13 ± 2.02 vs. 11.64 ± 1.93%, d = 2.06; and 34.25 ± 4.82 vs. 26.30 ± 4.23 (m²/s·cycle), d = 4.56, respectively). An association between mean velocity and intracycle IVV, CVV, and cycle rate (r = 0.68, 0.74 and 0.65, respectively) was observed in males but not in female single scullers (which may be attributed to anthropometric specificities). In female single scullers, mean velocity was related with distance per cycle and was associated with technical index in both males and females (r = 0.76 and 0.66, respectively). Despite these differences, male and female single scullers adopted similar pacing strategies and CVV remained constant throughout the 2000 m race (indicating that this variable might not be affected by fatigue). Differences were also observed in the velocity–time profile, with men reaching peak velocity first and having a faster propulsive phase. Data provided new information on how IVV and CVV relate to commonly used biomechanical variables in rowing. Technical index (r = 0.87): distance per cycle was associated with technical index in both males and females (r = 0.76 and 0.66, respectively). Future studies should include other boat classes and other performance variables such as the power output and arc length. Full article

The physiological and biomechanical characteristics of inline speed skating have not been systematically mapped nor research evidence synthesized. The aim was to identify and synthesize novel elements across studies, including participant characteristics, outcomes measures, experimental protocol, main outcomes and other relevant information, to inform evidence-based guidelines and recommendations. Following the PRISMA 2020 guidelines, a systematic search of databases was conducted to identify relevant studies. The extracted data were charted and synthesized to summarize the physiological and biomechanical aspects of inline speed skating. From 272 records, 22 studies met the defined criteria. Studies related to inline speed skating focused primarily on physiological variables (n = 14) and lower limb muscles function, with limited evidence on biomechanics of inline speed skating (n = 5) and the combination of biomechanics and physiology (n = 3). An overall unclear risk of bias was observed (59% of studies). Although studies have examined physiological and biomechanical variables, continuous physiological and biomechanical assessments of skaters performing different skills on both straight and curved tracks have not been conducted. Therefore, well-planned physiological and biomechanics studies are required to uncover underexplored areas in research and support the development of sport-specific studies. Full article

The rapid proliferation of wearable sensors and advanced tracking technologies has revolutionized data collection in elite sports, enabling continuous monitoring of athletes’ physiological and biomechanical states. This study proposes a comprehensive big data analytics framework that integrates data acquisition, processing, analytics, and decision support, demonstrated through synthetic datasets in football, basketball, and athletics case scenarios, modeled to represent typical data patterns and decision-making workflows observed in elite sport environments. Analytical methods, including gradient boosting classifiers, logistic regression, and multilayer perceptron models, were employed to predict injury risk, optimize in-game tactical decisions, and personalize sprint mechanics training. Key results include a 12% reduction in hamstring injury rates in football, a 16% improvement in clutch decision-making accuracy in basketball, and an 8% decrease in 100 m sprint times among athletes. The framework’s visualization tools and alert systems supported actionable insights for coaches and medical staff. Challenges such as data quality, privacy compliance, and model interpretability are addressed, with future research focusing on edge computing, federated learning, and augmented reality integration for enhanced real-time feedback. This study demonstrates the potential of integrated big data analytics to transform sports performance optimization, offering a reproducible and ethically sound platform for advancing personalized, data-driven athlete management. Full article

Background: Motion capture (MoCap) technologies have transformed athlete monitoring, yet athletic departments face complex decisions when selecting systems for multiple sports. Methods: We conducted a narrative review of peer-reviewed studies (2015–2025) examining optical marker-based, inertial measurement unit (IMU) systems, including Global Navigation Satellite System (GNSS)-integrated systems, and markerless computer vision systems. Studies were evaluated for validated accuracy metrics across indoor court, aquatic, and outdoor field environments. Results: Optical systems maintain sub-millimeter accuracy in controlled environments but face field limitations. IMU systems demonstrate an angular accuracy of 2–8° depending on movement complexity. Markerless systems show variable accuracy (sagittal: 3–15°, transverse: 3–57°). Environmental factors substantially impact system performance, with aquatic settings introducing an additional orientation error of 2° versus terrestrial applications. Outdoor environments challenge GNSS-based tracking (±0.3–3 m positional accuracy). Critical gaps include limited gender-specific validation and insufficient long-term reliability data. Conclusions: This review proposes a tiered implementation framework combining foundation-level team monitoring with specialized assessment tools. This evidence-based approach guides the selection of technology aligned with organizational priorities, sport-specific requirements, and resource constraints. Full article

Foot plantar pressure refers to the pressure or force that the foot generates in contact with the ground, varying across different regions of the foot. This parameter is essential in static and dynamic analyses to access accurate diagnoses, study the human body biomechanics, create functional footwear designs, aid in rehabilitation and physiotherapy, and prevent injuries in athletes during sports practice. This study presents an experimental comparison between two different plantar pressure measurement devices, Pedar^® (sensorized insoles) and Physiosensing^® (pressure platform). The devices were selected based on their capacity to measure contact area and peak pressure points. Results showed that Physiosensing^® provided a more uniform measurement of the contact area, proving its efficiency for weight distribution and stability analysis applications, particularly in posture assessment and balance studies. The Pedar^® system showed higher capacity in peak pressure point detection. Therefore, the insole system is more suitable for applications requiring precise high-pressure zone localization. Comparative analysis highlights the strengths and limitations of each device and offers insights regarding its optimal usage in clinical, sports, and research settings. Full article

Background/Objectives: Body stability plays a decisive role in archery, particularly during the aiming phase. A systematic review was conducted, in accordance with PRISMA guidelines, to critically examine the existing evidence on the association between body stability parameters and shooting performance. Methods: A comprehensive search of the MEDLINE Complete, CINAHL Complete, SportDiscus, and Cochrane Reviews databases was performed. Studies published until 12 July 2024 were considered. Results: Sixteen articles were selected, and we analyzed the following biomechanical parameters related to body stability: center of pressure displacement, velocity, and ellipse area; bow sway; and sway of markers placed on the head, sternum, and pelvis. The findings consistently showed that reduced center of pressure displacement and velocity, along with smaller center of pressure ellipse area, were associated with superior shooting outcomes. Although studies are scarce, data suggest that lower bow sway is associated with better shooting performance. The scarcity of research on the sway of markers placed in anatomical points does not allow for conclusions about their effectiveness as performance predictors. Despite its relevance, no studies have assessed the center of gravity data. Therefore, further research is needed to address this important point. Conclusions: Although studies have examined several parameters, the literature remains inconclusive regarding which of these parameters best predicts shooting quality. Full article

Against the backdrop of the deep integration of national fitness and sports science, this study addresses the lack of standardized movement assessment in yoga training by proposing an intelligent analysis system that integrates an improved YOLOv11-ECA detector with the DeepSORT tracking algorithm. A dynamic adaptive anchor mechanism and an Efficient Channel Attention (ECA) module are introduced, while the depthwise separable convolution in the C3k2 module is optimized with a kernel size of 2. Furthermore, a Parallel Spatial Attention (PSA) mechanism is incorporated to enhance multi-target feature discrimination. These enhancements enable the model to achieve a high detection accuracy of 98.6% mAP@0.5 while maintaining low computational complexity (2.35 M parameters, 3.11 GFLOPs). Evaluated on the SND Sun Salutation Yoga Dataset released in 2024, the improved model achieves a real-time processing speed of 85.79 frames per second (FPS) on an RTX 3060 platform, with an 18% reduction in computational cost compared to the baseline. Notably, it achieves a 0.9% improvement in AP@0.5 for small targets (<20 px). By integrating the Mars-smallCNN feature extraction network with a Kalman filtering-based trajectory prediction module, the system attains 58.3% Multiple Object Tracking Accuracy (MOTA) and 62.1% Identity F1 Score (IDF1) in dense multi-object scenarios, representing an improvement of approximately 9.8 percentage points over the conventional YOLO+DeepSORT method. Ablation studies confirm that the ECA module, implemented via lightweight 1D convolution, enhances channel attention modeling efficiency by 23% compared to the original SE module and reduces the false detection rate by 1.2 times under complex backgrounds. This study presents a complete “detection–tracking–assessment” pipeline for intelligent sports training. Future work aims to integrate 3D pose estimation to develop a closed-loop biomechanical analysis system, thereby advancing sports science toward intelligent decision-making paradigms. Full article

Background/Objectives: This review analyzes the effects of invasive and non-invasive methods of knee joint unloading on knee loading, employing a biomechanical model to evaluate their impact. Methods: PubMed, Web of Science, Cochrane, and Scopus were searched up to 15 May 2024 to identify eligible clinical studies evaluating Joint Space Width, Cartilage Thickness, the Western Ontario and McMaster Universities Osteoarthritis Index, the Knee Injury and Osteoarthritis Outcome Score system, Gait velocity, Peak Knee Adduction Moment, time to return to sports and to work, ground reaction force, and the visual analogue scale pain score. A second search was conducted to select a biomechanical model that could be parametrized, including the modifications that each treatment would impose on the knee joint and was capable of estimate joint loading to compare the effectiveness of each method. Results: Analyzing 28 studies (1652 participants), including 16 randomized clinical trials, revealed significant improvements mainly when performing knee joint distraction surgery, increasing Joint Space Width even after removal, and high tibial osteotomy, which realigns the knee but does not reduce loading. Implantable shock absorbers are also an attractive option as they partially unload the knee but require further investigation. Non-invasive methods improve biomechanical indicators of knee joint loading; however, they lack quantitative analysis of cartilage volume or Joint Space Width. Conclusions: Current evidence indicates a clear advantage in knee joint unloading methods, emphasizing the importance of adapted therapy. However, more extensive research, particularly using non-invasive approaches, is required to further understand the underlying knee joint loading mechanisms and advance the state of the art. Full article

This systematic review, registered in PROSPERO (CRD42025101243), aimed to evaluate how specific badminton shoe design features influence lower-limb biomechanics, injury risk, and sport-specific performance. A comprehensive search in six databases yielded 445 studies, from which 10 met inclusion criteria after duplicate removal and eligibility screening. The reviewed studies focused on modifications involving forefoot bending stiffness, torsional stiffness, lateral-wedge hardness, insole and midsole hardness, sole structure, and heel curvature. The most consistent biomechanical benefits were associated with moderate levels of forefoot and torsional stiffness (e.g., 60D) and rounded heel designs. Increased forefoot bending stiffness was associated with reduced foot torsion and knee loading during forward lunges. Torsional stiffness around 60D provided favorable ankle support and reduced knee abduction, suggesting potential protection against ligament strain. Rounded heels reduced vertical impact forces and promoted smoother knee–ankle coordination, especially in experienced athletes. Lateral-wedge designs improved movement efficiency by reducing contact time and enhancing joint stiffness. Harder midsoles, however, resulted in increased impact forces upon landing. Excessive stiffness in any component may restrict joint mobility and responsiveness. Studies included 127 male-dominated (aged 18–28) competitive athletes, assessing kinematics, impact forces, and coordination during sport-specific tasks. The reviewed studies predominantly involved male participants, with little attention to sex-specific biomechanical differences such as joint alignment and foot structure. Differences in testing methods and movement tasks further limited direct comparisons. Future research should explore real-game biomechanics, include diverse athlete populations, and investigate long-term adaptations. These efforts will contribute to the development of performance-enhancing, injury-reducing badminton shoes tailored to the unique demands of the sport. Full article

This study explores how artificial intelligence (AI) can support the evaluation of assistive technology outcomes in adaptive sports, focusing on elite boccia athletes with disabilities. Using a multi-stage motion analysis framework, we integrated OpenPose, ViTPose, and Lifting to estimate seated joint kinematics with greater precision. Match footage from 12 athletes at the 2018 Asia-Pacific Boccia Open was analyzed across five biomechanical phases: preparation, acceleration, peak, release, and follow-through. AI-enhanced 2D and 3D pose estimation methods were applied to assess throwing strategies and motor variability. ViTPose outperformed OpenPose in joint detection accuracy (F1-score: 85% vs. 79.5%), while Lifting improved 3D estimation by reducing joint position error by 16%. Principal Component Analysis revealed greater movement consistency in overhand throws compared to underhand techniques. The proposed pipeline provides an interpretable and scalable method for measuring performance, motor control, and strategy-specific movement outcomes in boccia, offering practical applications for evidence-based coaching, athlete classification, and the design of inclusive assistive sport technologies. Full article

Objectives: This study aimed to compare the involuntary stimulated neuromuscular response of thigh muscles in karate subgroups and non-athletes. We investigated whether karate training creates neuromuscular adaptations and if the synchronization of knee flexor and extensor muscles in karate practitioners is level-dependent. Methods: The study included 7 elite karate athletes (KE), 14 sub-elite karate athletes (KSE), 16 individuals with basic karate training (KB), and 14 non–athletes (NA). Tensiomyographic (TMG) measurements were obtained from the rectus femoris, vastus medialis, vastus lateralis, biceps femoris, and semitendinosus muscles. Indexes of Intermuscular Synchronization (IIS) were calculated for contraction time (Tc), total contraction time (TcT), and rate of muscle tension development (RMTD) as variables for the observed muscles of a given muscle group (extensors of the dominant leg, flexors of the dominant leg, extensors of the non-dominant leg, and flexors of the non-dominant leg). Results: Statistically significant differences were observed in the intermuscular synchronization indexes between karate experience levels and non-athletes. Compared to non-athletes, elite (KE), sub-elite (KSE), and beginner karateka (KB) all demonstrated shorter contraction time indexes in dominant knee extensors (p = 0.042, 0.040, and 0.013, respectively). In the non-dominant flexors, KE exhibited significantly better synchronization than KSE (p = 0.001), KB (p = 0.033), and NA (p = 0.002). For the total contraction time index, both KSE and KB outperformed NA in dominant extensors (p = 0.023 and p = 0.008), while KE showed superiority in non-dominant extensors and flexors compared to all other groups (p-values ranging from 0.002 to 0.038). Significant RMTD differences were found in the dominant leg between KE and KSE (p = 0.036) and KE and KB (p = 0.001), as well as in the non-dominant leg between KE and KB (p = 0.011) and KE and NA (p = 0.025). These findings were accompanied by statistical powers exceeding 0.80 in most cases, underscoring the robustness of the observed differences. Conclusions: These findings highlight that muscle coordination patterns, as revealed through non-invasive TMG-based indexes, are sensitive to training level and laterality in karate practitioners. Importantly, elite athletes demonstrated more synchronized activation in key muscle groups, suggesting a neuromuscular adaptation specific to high-level combat sports. From a biomechanical perspective, improved intermuscular synchronization may reflect optimized neural strategies for stability, speed, and efficiency—key components in competitive karate. Thus, this method holds promise not only for performance diagnostics but also for refining individualized training strategies in combat sports and broader athletic contexts. Full article

This study aimed to explore the independent and interactive effects of varying squat depths and movement speeds on dynamic postural stability during the Part the Wild Horse’s Mane (PWHM) movement. Thirteen male participants (age: 25.86 ± 1.35 years; height: 174.26 ± 6.09 cm; body mass: 68.64 ± 8.15 kg) performed the PWHM movement at three different squat heights, high squat (HS), middle squat (MS), low squat (LS), and two different speeds, fast and slow. Dynamic postural stability (DPSI) was assessed through the center-of-mass (CoM) trajectory and the center-of-pressure (CoP) trajectory. The analyses used two-factor repeated-measures ANOVA and statistical nonparametric mapping, with key metrics including anteroposterior stability (APSI), mediolateral stability (MLSI), vertical stability (VSI), DPSI indices, and the path lengths of the CoP and CoM. LS exhibited significantly greater CoP and CoM path lengths compared with MS and HS (p < 0.01). Furthermore, fast movements demonstrated higher VSI and DPSI than slow movements (p < 0.05). Tai Chi with different squat depths and speeds can affect postural stability. To reduce the fall risk, older adults and individuals with balance impairments should prioritize slower Tai Chi movements, particularly when using high squat postures. Full article

The knee is one of the most frequently injured joints, involving various structures. To prevent reinjury after rehabilitation, braces are commonly used. However, most studies on knee supports focus on subjects with anterior cruciate ligament (ACL) injuries and do not account for muscle fatigue, which typically occurs during prolonged intense training and can significantly increase the risk of injury. Hence, this study investigates the acute effects of wearing a knee brace on biomechanics in subjects with a history of various unilateral knee injuries or pain under muscle fatigue. In total, 50 subjects completed an intense fatigue protocol and then performed counter-movement jumps and running tests on a force plate while tracking kinematics with a marker-based 3D motion analysis system. Additionally, subjects filled out a visual analog scale (VAS) to assess knee pain and stability. Tests were conducted on the injured leg with and without a knee brace (Sports Knee Support, Bauerfeind AG, Zeulenroda-Triebes, Germany) and on the healthy leg. Results indicated that wearing the knee brace stabilized knee movement in the frontal plane, with a significant reduction in maximal medio-lateral knee acceleration and knee abduction moment during running and jumping. The brace also normalized loading on the injured leg. We observed higher maximal knee flexion moments, which were associated with increased vertical ground reaction forces, segment velocities, and knee flexion angles. Subjects reported less pain and greater stability while wearing the knee brace. Therefore, we confirm that wearing a knee brace on the injured leg improves joint biomechanics by enhancing stability and kinematics and reducing pain during running and jumping, even with muscle fatigue. Consequently, wearing a knee brace after a knee joint injury may reduce the risk of reinjury. Full article