Identification method of long-distance running injury points for college students based on association rules

Abstract

In view of the weak correlation between the signal features of the sports injury image extracted by the existing methods and the damage points, the accuracy is low and the recognition time is long. In order to improve the recognition accuracy of sports injury and reduce the loss of sports injury to human body, a method of college students’ long-distance running injury point recognition based on association rules is proposed. According to the contour of the injured part of college students’ long-distance running, the image is segmented, and the wavelet function is used to decompose the image signal into different frequency bands. The strong correlation rules between the wavelet function and the image signal are analyzed, so that the total energy of the time domain waveform can replace the wavelet transform coefficient; Secondly, the laser harmonic imaging points which have strong correlation with the damage points are regarded as the damage points; Finally,construct the perspective image acquisition platform, collect the sports injury image data of College Students’ long-distance runners in sports school, and set up comparative experiments. The experimental results show that the design method improves the recognition accuracy of College Students’ long-distance sports injury points and reduces the recognition time.