58 2026 TSMA deep learning and pattern recognition capabilities are ushering us into a new era of ‘movement understanding’. Through massive motion databases, AI can not only identify what movements you made, but also infer why you made them, predict possible future performance changes, and identify risks. Three Core AI Technologies 1. Enhanced Pose Estimation: AI strengthens recognition accuracy and speed, making motion analysis more precise and stable. 2. Motion Pattern Recognition: Identifies unique strategies and habitual movement styles, distinguishing effective from risky compensations. 3. Predictive Modeling and Real-Time Coaching: Combines sensor data with historical data to forecast fatigue, motion deterioration, and training responses. Application Scenario 1: Performance Optimization and Personalized Training In professional sports, AI analysis strengthens athletes’ techniques and efficiency. For instance, in sprinting, AI can analyze start acceleration, step frequency, and muscle activation timing to identify key factors affecting explosiveness and suggest technical or strength improvements. AI is also applied in tennis and golf to reconstruct swing motions. It not only detects racket trajectory deviations but also recommends optimal swing strategies based on shot outcomes and opponent responses, gradually building a ‘data-driven decision-making mindset’ for athletes. Application Scenario 2: Motion Anomaly Detection and Injury Prediction AI systems learn from hundreds of athletes’ pre-injury data patterns to create a ‘high-risk model’ database. When a user’s motion approaches these risky templates, the system issues early warnings. For example, if a basketball player ’s left foot ground contact time keeps lengthening, knee inward angles increase, and RPE values rise disproportionately over two weeks, AI may flag a heightened ACL injury risk and suggest rest, position adjustments, or reducing intensity. Application Scenario 3: Remote Coaching and Real-Time Feedback Systems In-home training and remote rehabilitation, AI is evolving from post-training review to ‘real-time instructor’. Platforms like Tonal and Peloton already combine AI motion recognition with voice systems
RkJQdWJsaXNoZXIy MjIwMjA1