Search Results (79)

The integration of sensor technology and artificial intelligence is revolutionizing athletic training. This paper presents a novel cost-effective smart table tennis racket embedded with a nine-axis inertial measurement unit (IMU) for real-time stroke classification directly on the device. Unlike systems that are reliant on external computation, our approach leverages Tiny Machine Learning (TinyML) to deploy a customized Convolutional Neural Network (CNN) model onto a microcontroller unit (STM32F7), enabling real-time inference at the edge. The system captures accelerometer and gyroscope data, which is automatically segmented via a recursive algorithm and classified into six fundamental strokes (e.g., forehand/backhand stroke, pull, and chop) or a non-swing state. The classified results are wirelessly transmitted to a computer application for real-time feedback. Experimental results with actual players demonstrate that the optimized CNN model achieves an average classification accuracy of 98.3% in controlled tests and over 94% in mixed-stroke scenarios, validating the system’s high accuracy and robustness. This work exemplifies the practical implementation of an end-to-end intelligent sensor system, highlighting the potential of TinyML to enable advanced, low-power motion analysis in sports. Full article

(1) Background: The aim of this study was to determine the biomechanical role of plantar pressure distribution in generating racket velocity during the topspin forehand in table tennis players, with particular emphasis on its relationship with stroke kinematics and performance level. (2) Methods: The study involved 14 male table tennis players divided into Elite and Sub-Elite athletes. Each participant performed a topspin forehand stroke. The study employed a biomechanical analysis combining inertial motion capture and plantar pressure measurement to assess the relationship between lower limb loading and racket velocity during the topspin forehand. (3) Results: The statistical evidence supports the subsequent phase-by-phase comparisons, indicating that the Elite (EL) and Sub-Elite players (SE) differ in execution of the topspin forehand, and the Elite group achieved significantly higher racket speed values in all phases (e.g., in hitting phase: SE-13.8 m/s, EL-15.6 m/s, p ≤ 0.001, d = 1.0; in post-impact follow-through phase: SE-13.8 m/s, El-16.1 m/s, ≤0.001, d = 1.3) and exhibited also a different pattern of foot loading. An analysis of the correlation between the plantar pressure and velocity of the racket in individual events revealed numerous significant correlations. (4) Conclusions: The study identified numerous correlations between the maximum plantar pressure and the maximum racket speed in the individual phases of the stroke. This demonstrates the active involvement of the feet throughout the entire kinematic chain of the topspin forehand stroke and highlights the importance of foot coordination for the outcome of this stroke, namely the speed of the racket-wielding arm. Full article

A backhand flick is frequently used in table tennis to initiate offensive play, yet how racket motion evolves during subsequent stroke transitions remains insufficiently characterized. This study examined racket kinematics in two common follow-up combinations: a backhand flick followed by a backhand fast block (BFBB) and a backhand flick followed by a forehand fast block (BFFB). In a within-subject design, ten national-level male players performed both combinations, and racket motion was recorded using a three-dimensional motion capture system at 200 Hz. Racket velocity, phase duration, and spatial displacement were quantified across the stroke sequence, and within-player differences between the two stroke transition combinations following the backhand flick were examined. Compared with BFBB, BFFB showed higher racket velocity at most key moments, particularly near ball contact, whereas no significant difference was found at the end of the follow-through. Backward-phase duration did not differ between the two conditions, but BFFB showed longer durations during the hitting and follow-through phases, together with a longer overall duration. BFFB also exhibited greater directional displacement across multiple phases, whereas BFBB was characterized by a more compact spatiotemporal pattern. These findings provide biomechanical evidence that different follow-up strokes after an identical backhand flick are associated with distinct patterns of racket motion during stroke transitions and may offer a kinematic reference for sequence-specific training in table tennis. Full article

Mobile EEG enables investigating brain activity during real-world behaviour, but remains susceptible to motion artefacts, limiting signal interpretability and the use of advanced analytical techniques. Methods developed for removing motion-related artefacts induced by periodic activity like cycling, walking or juggling showed degraded performance with increasing movement variability and speed. To fill this gap, we developed a method based on generalized eigenvalue decomposition (GED) to identify and suppress highly variable, non-periodic—especially transient—artefacts due to very rapid, free full body movements of different types, as they occur during sports practice. By leveraging the contrast between covariance matrices of artefactual and resting-state EEG segments, this approach isolates motion-related components for removal during multichannel EEG signal reconstruction. The method was validated on two ecological datasets featuring stereotyped head and body movements and dynamic table tennis. Comparison with state-of-the-art technique showed superior performance of our method in terms of signal-to-error ratio (SER), artefact-to-residue ratio (ARR), brain spectral power preservation and computation time. Sensitivity analysis was applied to demonstrate the method’s robustness to parameter changes. These findings highlight the potential of the proposed method as a robust, generalizable approach for motion artefact suppression in mobile EEG, particularly when applied in extreme recording conditions like during active sports activity. Full article

Visual attention involves the efficient allocation of processing resources across space and under conditions of visual competition. This study examined whether experience-related advantages in visual attention are expressed uniformly or selectively across attentional components. Using a modified Useful Field of View (UFOV) paradigm, four groups with distinct experiential backgrounds were compared: table tennis players (TTPs), action video game players (AVGPs), aerobic gymnastics athletes (AGAs), and non-trained college students (NCSs). Subtest 1 assessed central identification under relatively low attentional control demands. No significant group differences were observed, indicating comparable basic central identification performance across groups. Subtests 2 and 3 assessed divided attention and selective attention under interference, respectively. In Subtest 2, all experienced groups outperformed NCSs, with no differences among TTPs, AVGPs, and AGAs. In Subtest 3 under high visual competition, performance diverged; TTPs and AVGPs outperformed both AGAs and NCSs, whereas AGAs did not differ from controls. These findings indicate that experience-related advantages in visual attention are component-specific rather than global, and become most evident when tasks place stronger demands on attentional control under interference. The advantage pattern shown by TTPs under higher attentional control demands was more compatible with visually demanding experience than with physical training alone. No significant interactions with eccentricity were observed, suggesting consistent group differences across peripheral distances. Full article

Quantitative evaluation of human motion from image data requires both high geometric precision and mathematical interpretability. To address the limitations of pixel-level posture analysis and empirical performance scoring, this study proposes a geometry-driven quantitative modeling framework for image-based motion evaluation. Sub-pixel edge detection based on quadratic polynomial interpolation is first employed to construct a precise continuous representation of limb contours from image sequences. By abstracting the human arm as a spatial rigid-body system, posture evaluation is reformulated as an optimization problem governed by geometric constraints and physical principles. An optimal swing trajectory is obtained by minimizing the total kinetic energy of the system, which is solved numerically using Newton’s iterative method, avoiding the explicit solution of highly coupled inverse kinematics. To further analyze the contribution of multiple performance-related variables within a unified quantitative framework, a hybrid feature attribution strategy integrating Random Forest, XGBoost, and LightGBM is introduced. The proposed mixed feature mining approach reduces model dependency and enhances the robustness of factor importance ranking. The effectiveness of the proposed framework is validated using image data collected from a cloud-based table tennis classroom. The experimental results demonstrate that the geometry-driven modeling approach provides stable, interpretable, and discriminative evaluation outcomes, indicating its potential applicability to broader image-based human motion analysis tasks. Full article

This study addresses the issue of inaccurate results in traditional table tennis player classification, which is often influenced by subjective judgment and environmental factors, by proposing a youth table tennis player classification system based on sensor fusion and the random forest algorithm. The system utilizes an embedded intelligent table tennis racket equipped with an ICM20948 nine-axis sensor and a wireless transmission module to capture real-time acceleration and angular velocity data during players’ strokes while synchronously employing a camera with OpenPose to extract joint angle variations. A total of 40 players’ stroke data were collected. Due to the limited sample size of top-tier players, the Synthetic Minority Over-sampling Technique (SMOTE) was applied, resulting in a final dataset of 360 records. Multiple key motion indicators were then computed and stored in a dedicated database. Experimental results showed that the proposed system, powered by the random forest algorithm, achieved a classification accuracy of 91.3% under conventional cross-validation, while subject-independent LOSO validation yielded a more conservative accuracy of 70.89%, making it a valuable reference for coaches and referees in conducting objective player classification. Future work will focus on expanding the dataset of domestic high-performance athletes and integrating precise sports science resources to further enhance the system’s performance and algorithmic models, thereby promoting the scientific selection of national team players and advancing the intelligent development of table tennis. Full article

This study proposes an integrated agility assessment system that combines Millimeter-Wave (MMW) radar, Ultra-Wideband (UWB) ranging, and Mixed Reality (MR) technologies to quantitatively evaluate athlete performance with high accuracy. The system utilizes the fine motion-tracking capability of MMW radar and the immersive real-time visualization provided by MR to ensure reliable operation under low-light conditions and multi-object occlusion, thereby enabling precise measurement of mobility, reaction time, and movement distance. To address the challenge of player identification during doubles testing, a one-to-one UWB configuration was adopted, in which each base station was paired with a wearable tag to distinguish individual athletes. UWB identification was not required during single-player tests. The experimental protocol included three specialized agility assessments—Table Tennis Agility Test I (TTAT I), Table Tennis Doubles Agility Test II (TTAT II), and the Agility T-Test (ATT)—conducted with more than 80 table tennis players of different technical levels (80% male and 20% female). Each athlete completed two sets of two trials to ensure measurement consistency and data stability. Experimental results demonstrated that the proposed system effectively captured displacement trajectories, movement speed, and reaction time. The MMW radar achieved an average measurement error of less than 10%, and the overall classification model attained an accuracy of 91%, confirming the reliability and robustness of the integrated sensing pipeline. Beyond local storage and MR-based live visualization, the system also supports cloud-based data uploading for graphical analysis and enables MR content to be mirrored on connected computer displays. This feature allows coaches to monitor performance in real time and provide immediate feedback. By integrating the environmental adaptability of MMW radar, the real-time visualization capability of MR, UWB-assisted athlete identification, and cloud-based data management, the proposed system demonstrates strong potential for professional sports training, technical diagnostics, and tactical optimization. It delivers timely and accurate performance metrics and contributes to the advancement of data-driven sports science applications. Full article

This study investigated the kinematic characteristics of center of mass (CoM) movement in elite standing para table tennis players during a controlled 20-ball displacement speed test, focusing on displacement, velocity, acceleration, and jerk as indicators of movement coordination and control. Twenty-one national-level athletes (classes 6–11) performed alternating forehand and backhand strokes while three-dimensional motion analysis captured CoM trajectories. The primary aim was to characterize directional CoM kinematics, and the secondary aim was to examine associations with functional ability, stroke accuracy, and expert-rated technical performance. Results indicated that the range of CoM displacement was largest in the medio-lateral direction, reflecting the sport-specific demands of side-to-side repositioning, while mean displacement did not differ significantly between the medio-lateral and antero-posterior axes. Similarly, velocity, acceleration, and jerk ranges were greatest laterally, highlighting the dynamic requirements of lateral movement. Correlation analyses revealed no statistically significant associations between CoM metrics and functional ability, stroke accuracy, or expert-rated performance after Bonferroni correction, though exploratory trends suggested that higher-functioning athletes may exhibit greater lateral displacement. Jerk, as a measure of movement smoothness, did not systematically differentiate performance or functional class. These findings underscore the predominance of lateral CoM control in para table tennis and provide a biomechanical basis for training interventions aimed at improving lateral stability, coordination, and functional efficiency. Full article

Background/Objectives: This study examined the effects of a six-week eccentric–reactive training program on neuromechanical markers of lateral explosiveness, asymmetry, and stretch-shortening cycle (SSC) efficiency in elite male youth table tennis players. Fourteen national-level athletes (mean age = 16.6 years) were assigned to either an experimental group (EG, n = 7) or a control group (CG, n = 7). EG performed flywheel squats and lateral depth jumps three times per week, while CG maintained regular training. Pre- and post-intervention testing included countermovement jumps, reactive strength index (RSI_DJ), force asymmetry, time-to-stabilization, SSC efficiency, and energy transfer ratio (ETR), measured via force plates, EMG, and inertial sensors. Methods: Multi-dimensional statistical analysis revealed coordinated improvements in explosive power and movement efficiency following eccentric training that were not visible when examining individual measures separately. Athletes in the training group showed enhanced neuromechanical control and developed more efficient movement patterns compared to controls. The analysis successfully identified distinct performance profiles and demonstrated that the training program improved explosive characteristics in elite table tennis players. Results: Univariate ANOVAs showed no significant Group × Time effects for RSI_DJ, ETR, or SSC_Eff, although RSI_DJ displayed a moderate effect size in EG (d = 0.47, 95% CI [0.12, 0.82], p = 0.043). In contrast, MANOVA confirmed a significant multivariate Group × Time interaction (p = 0.013), demonstrating integrated neuromechanical adaptations. Regression analysis indicated lower baseline CMJ and RSI_DJ predicted greater RSI improvements. Conclusions: In conclusion, eccentric–reactive training promoted multidimensional neuromechanical adaptations in elite racket sport athletes, supporting the use of integrated monitoring and targeted eccentric loading to enhance lateral explosiveness and efficiency. Full article

Table tennis (TT) is a high-speed sport requiring integrated cognitive and motor skills. However, the existing assessment tools have failed to replicate its sport-specific demands. Therefore, this study aimed to evaluate the validity and reliability of the Reactive Table Tennis test designed to assess cognitive–motor performance in TT. Sixty athletes were recruited from TT, combat sports (CS), team sports (TS), and track and field (TF). Participants were required to react to 10 visual stimuli randomly emitted from three devices placed 3 m frontally by performing 1.5 m lateral or frontal displacements. Athletes passed through a timing gate using either both hands (B) or only one hand (O) under two conditions: with consecutive stimulus presentation (C) and with a 0.8 s delay between stimuli (D), simulating the typical inter-shot time observed during the rallies. Each participant completed three trials per condition on three non-consecutive days. Results showed the highest reliability under the delayed conditions (ICC_BD = 0.969; ICC_OD = 0.961), along with lower coefficients of variation than for the consecutive conditions. TT players performed significantly faster (p < 0.05) than other athletes under BD, OD, and BC but not under OC conditions. The mean of three trials is recommended for more accurate assessments. The proposed test proved to be a valid and reliable tool, especially under the both hand-delay condition, and is suitable for large-scale use in TT. Full article

Operative medicine needs fine manual skills; therefore, several educational training programs focus on skill development as well. Related to sports sciences, various sport types are also dependent on fine motor skills. We hypothesized that an adequate sport training program may contribute to the development of medical students’ manual dexterity. We conducted objectively tests using high-fidelity medical simulators. Volunteer medical students were delegated to table tennis group (TG), where students participated in 2 h/week of table tennis training for 7 weeks, or to a Control group (CG) that included students without regular sport activity. Objective data on fine motor skills during completion of basic modules of high-fidelity vascular catheterization and arthroscopy simulators were recorded before and after the 7-week period. In the TG group, significant differences were found in time and quality parameters compared to CG. On the vascular catheterization simulator basic navigation module, all time parameters improved. On the arthroscopy simulator basic skill module, the total performance and safety scores significantly improved, and procedure time decreased. In conclusion, high-fidelity vascular catheterization and arthroscopy medical simulators with basic training modules could provide useful feedback for fine motor skill development. The intensive table tennis training program was effective in maintaining/improving medical students’ fine manual skills. Full article

This paper investigates the relationship between ball spin and linear speed in table tennis. This study uses a simple photodiode montage to introduce a methodology for measuring spin based on light reflection on the ball’s surface. Two optical-based measurement systems were developed to measure either the ball’s speed or spin. This paper describes sensor calibration and error estimation. Those systems measured ball kinetic parameters from nine young elite players (aged 15 ± 1.5 years) who volunteered to perform 4 exercises. Results showed a strong positive linear relationship between the ball’s speed and spin (r = 0.96, R² = 0.93, p < 0.001). The effect of exercise conditions on ball speed has been studied using a statistical test, ANOVA. Results showed a significant main effect of exercise conditions on ball speed (p < 0.05) with a very large effect size (η² = 0.82). The study revealed significant variations in linear speed based on the type of stroke (backhand, forehand) and the incoming ball’s spin (topspin, backspin), with topspin forehand strokes achieving higher speeds compared to backhand strokes. These findings provide valuable knowledge for players to enhance performance in a competitive environment. Full article

The adoption of artificial intelligence (AI) in sports training has the potential to revolutionize skill development, yet cost-effective solutions remain scarce, particularly in table tennis. To bridge this gap, we present an intelligent training system leveraging computer vision and machine learning for real-time performance analysis. The system integrates YOLOv5 for high-precision ball detection (98% accuracy) and MediaPipe for athlete posture evaluation. A dynamic time-wrapping algorithm further assesses stroke effectiveness, demonstrating statistically significant discrimination between beginner and intermediate players (p = 0.004 and Cohen’s d = 0.86) in a cohort of 50 participants. By automating feedback and reducing reliance on expert observation, this system offers a scalable tool for coaching, self-training, and sports analysis. Its modular design also allows adaptation to other racket sports, highlighting broader utility in athletic training and entertainment applications. Full article

Background/Aims: Table tennis performance is influenced by various factors such as technique, tactics, and fitness. Additionally, many shots are executed at high speeds, developing significant levels of explosive strength in the lower extremities. This study aimed to assess the jump capacity and the elasticity index of the lower limbs among young table tennis players based on sex. Additionally, this study assessed leg asymmetries between the dominant and non-dominant limbs during jump tests. Methods: A total of 40 players (20 boys and 20 girls), aged 16–18 years, participated in the study. Vertical countermovement jump, squat jump, and horizontal jump tests were conducted to evaluate both vertical and horizontal jumping capacities, as well as leg asymmetries between the dominant and non-dominant limbs. Results: Differences were observed in both vertical and horizontal jumps, with male players achieving better results in all jumping capacities. However, female players obtained better values in elastic index. Additionally, significant differences were found between dominant and non-dominant legs in both male and female players. Conclusions: Considering that explosive strength is one of the most essential physical capacities in this sport, this information could prove valuable for talent identification, the design of training programs, and the optimization of physical performance monitoring systems in table tennis. Full article