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CNN sensor based motion capture system application in basketball training and injury prevention
1College of Physical Education, Kunshan National University, Kunshan, Jeollabuk-do 54150, Republic of Korea; College of Physical Education, Jilin Normal University, Siping, Jilin 136000, China.
Preventive Medicine
|July 22, 2023
Summary
This study introduces a CNN sensor-based motion capture system for real-time basketball player monitoring. It aids in preventing sports injuries by analyzing movement data for timely alerts and improved training.
Area of Science:
- Sports Science
- Biomechanical Engineering
- Artificial Intelligence in Sports
Background:
- Basketball is a high-intensity sport with a high incidence of injuries.
- Real-time monitoring of athlete status is crucial for injury prevention and performance optimization.
- Current methods may lack the precision needed for timely intervention.
Purpose of the Study:
- To propose a novel motion capture system utilizing Convolutional Neural Network (CNN) sensors.
- To enable real-time monitoring of basketball players' physiological and biomechanical data.
- To enhance the accuracy and effectiveness of sports injury detection and prevention.
Main Methods:
- Development of a motion capture system integrating CNN sensors.
- Real-time collection of athlete movement data including track, speed, acceleration, stride frequency, heart rate, and energy consumption.
- Application of CNN for processing and analyzing collected motion data to identify injury risks.
Main Results:
- The CNN-based system achieves high precision and accuracy in motion data analysis.
- The system provides real-time alerts for potential sports injuries.
- Comprehensive, scientific, and real-time sports data is generated for athletes and coaches.
Conclusions:
- The CNN sensor-based motion capture system effectively monitors and prevents sports injuries in basketball.
- The system offers valuable data to improve training strategies and tactical adjustments.
- Enhanced player safety and competitive performance are key outcomes of this technology.
