57 Taiwan Sporting Goods Manufacturers Association A systematic review published in the European Journal of Sport Science in 2019 found that combining sensor data with AI models could predict athletes’ recovery times and injury risks under specific intensities. This is especially meaningful for athletes competing in continuous events such as the World Cup or the Olympics. In basketball, IMUs embedded in vests capture jump height, sudden stops, and coordination, providing scientific decision-making data for technical coaches. Application Scenario 2: Running Injury Prevention and Training Optimization For the vast population of runners and marathoners, the greatest value of sensors lies in predicting and preventing overuse injuries. Modern smart shoes and socks with embedded pressure and acceleration modules detect gait deviations like excessive pronation or asymmetric landing angles, and recommend cadence adjustments or shoe choices accordingly. When accumulated mileage is too high, the system can automatically suggest recovery measures such as delaying the next high-intensity workout, adding stretching days, or cross-training. Application Scenario 3: Elderly Health Promotion and Remote Care Wearable sensors are not limited to young athletes—they also have immense potential in elderly health monitoring. Smart insoles can measure step stability and ground reaction forces in daily activities, marking periods of unstable gait for caregivers to predict fall risks. Combined with EMG patches and smartwatches, they can also track muscle activity decline, enabling timely introduction of strength training programs. 3. AI-Assisted Analysis and Prediction: From Data to Insights AI applications in sports science have already surpassed simple statistics or visualization. Its
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