Treadmill Motion Monitoring System Based on Edge Computing and Deep Learning
This article provides an intelligent monitoring solution for treadmill enthusiasts,providing comprehensive motion analysis and guidance.The system combines facial heart rate monitoring and running posture recognition functions,and collects user video data through a camera to achieve non-contact heart rate monitoring,providing users with real-time physiological information to optimize exercise intensity and rhythm;A deep learning algorithm is used to identify key posture elements of runners,such as shoulder balance,arm swing,and landing posture,to improve running skills and reduce exercise risks.This research organically combines edge computing and deep learning technology,providing new directions and opportunities for innovation in the field of sports health.
万方数据
维普
