AIMC Topic: Athletic Performance
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Automatic video analysis of countermovement jump performance using a single uncalibrated camera.
Journal of biomechanics
Apr 12, 2025
The countermovement jump (CMJ) assessment is widely employed for monitoring sports performance, traditionally relying on heavy and expensive force plates to extract performance variables like jump height and peak force. Inertial measurement unit (IMU...
Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports.
Sensors (Basel, Switzerland)
Apr 3, 2025
Over the past four decades, cheerleading evolved from a sideline activity at major sporting events into a professional, competitive sport with growing global popularity. Evaluating tumbling elements in cheerleading relies on both objective measures a...
Neural networks can accurately identify individual runners from their foot kinematics, but fail to predict their running performance.
Journal of biomechanics
Apr 2, 2025
Athletes and coaches may seek to improve running performance through adjustments to running form. Running form refers to the biomechanical characteristics of a runner's movement, and can distinguish individual runners as well as groups of runners, su...
Footwork recognition and trajectory tracking in track and field based on image processing.
Scientific reports
Mar 28, 2025
In track and field sports, footwork can greatly affect the effect and performance of sports. Accurate footwork can effectively improve the performance of professional athletes, and for ordinary trainers, it can reduce the probability of training inju...
Predicting badminton outcomes through machine learning and technical action frequencies.
Scientific reports
Mar 27, 2025
The application of machine learning techniques to predict badminton match outcomes through the analysis of technical actions seems to represent an area that has not yet been extensively investigated within the existing body of research. This study ai...
Investigating the increase in the specialized performance of athletes using artificial neural network (ANN) exercises.
Scientific reports
Mar 12, 2025
Badminton, a dynamic and fast-paced racket sport, demands a unique combination of physical, technical, and cognitive abilities from its players. This study investigates the impact of a tailored core strength training program on the specialized perfor...
Leveraging graph neural networks and gate recurrent units for accurate and transparent prediction of baseball pitching speed.
Scientific reports
Mar 5, 2025
Long short-term memory (LSTM) networks are widely used in biomechanical data analysis but have the significant limitations in interpretability and decision transparency. Combining graph neural networks (GNN) with gate recurrent units (GRU) may offer ...
Table tennis coaching system based on a multimodal large language model with a table tennis knowledge base.
PloS one
Feb 13, 2025
UNLABELLED: Table tennis is one of the most popular sports in the world, and it plays a positive role in the overall development of people's physical and mental health. This study develops an AI table tennis coaching system using a Multimodal Large L...
Subjective recovery in professional soccer players: A machine learning and mediation approach.
Journal of sports sciences
Feb 5, 2025
Coaches often ask players to judge their recovery status (subjective recovery). We aimed to explore potential determinants of subjective recovery in 101 male professional soccer players of 4 Italian Serie C teams and to further investigate whether th...
A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness.
Scientific reports
Jan 25, 2025
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the ef...
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