Rehabilitation Assistance System for Limb Motor Function Based on Deep Learning

Abstract

With the development and dissemination of the concept of smart medical care, people's attention to their own health and smart medical system is gradually increasing. In medical activities, the rehabilitation assistance system is very important for patients, and the family and entertainment of the rehabilitation assistance system is the general trend. At the same time, the role of the rehabilitation assistance system is largely affected by its algorithm and function settings. Therefore, it is necessary to introduce deep learning (DL) algorithms to optimize the rehabilitation assistance system. In view of the above problems, this paper used the pre-training label pre-judgment algorithm and the sample classification training method to conduct scientific research and analysis on the limb motor function rehabilitation assistance system. At the same time, a new rehabilitation assistance system including signal acquisition system, local monitoring system and medical center monitoring system was designed. The results of the experimental test showed that this new limb motor function rehabilitation assistance system could better collect the user's biological signals because of the addition of DL. The recognition of the signal has been improved to an accuracy of about 45%, which showed that the research on the rehabilitation assistance system of limb motor function based on DL could better provide unique services for the rehabilitation of patients.