Study and experimental analysis of the effect of static stretching combined with resistance training on neck and shoulder syndrome in college students in the context of big data

Abstract

Abstract In order to explore the effect of variable resistance training with edge computing and information physical system model combined with computer vision under static traction in neck and shoulder rehabilitation training of college students. In this paper, 90 cases of neck and shoulder patients admitted to XX Hospital from February 2022 to December 2022 with neck and shoulder syndrome in a university in Shanghai, were selected as study subjects and randomly divided into 45 cases of the observation group and 45 cases of the control group. Edge computing and physical information system were used for data processing, and patients in the observation group received variable resistance training combined with static traction, and patients in the control group received static traction. The results showed that after rehabilitation training, the effective rates of the observation group and the control group were 91.11% and 71.11%, respectively, and the differences between the groups were statistically significant (P<0.05). Comparing the visual analog scale (VAS) and neck disability index (NDI) of the two groups, the VAS score of the observation group was lower than that of the control group after treatment (P<0.05), and the NDI score of the observation group was lower than that of the control group (P<0.05). It indicates that the use of static stretching and resistance training for neck and shoulder syndrome in college students is more effective in relieving patients’ neck pain and is worthy of clinical promotion and application.