Health Index Monitoring of Sports Injury Rehabilitation Training Based on Wearable Sensors.

Jiang Yi,Yuepei Zou

doi:10.1155/2021/6302991

Abstract

In order to design the perception system of the lower limb wearable rehabilitation robot, this study established the kinematics theoretical model of human lower limb and conducted the kinematics analysis of human body. By using the dynamic attitude analysis system, combined with the human body mark points, the position data of human body mark points in the process of standing up, sitting up, walking, stepping up, and squatting were collected. Combined with the movement mechanism of human lower limbs, the characteristics of human motion state transition are analyzed, and the perceptual algorithm for judging human motion intention is studied, so as to determine the wearer's current posture, standing intention while sitting, walking intention while standing, moving intention, and stopping intention during walking. The results show that the angle of the hip joint changes regularly between 0° and 37° and the angle of the knee joint changes regularly between 0° and 70°during the standing process, which is consistent with the angle change trajectory collected by the dynamic attitude analysis system. The angle trajectories of the hip and knee joints measured by the absolute angle sensor are the same as those obtained by the dynamic attitude analysis system. 1.5 rad and 0.3 rad were selected as reasonable and effective thresholds for determining sitting and standing states.

Highlights

In the field of nervous system diseases, some progress has been made in the research on the rehabilitation of the central nervous system (CNS)
Experts have found that the central nerves such as the brain and spinal cord can stimulate the nervous system of the lost limbs through repeated learning and training in a passive form, so that its function is restored and strengthened [1]. erefore, an auxiliary system can be developed to drive the limbs to carry out repeated training and develop the potential learning function of the limbs. e higher the intelligent degree of the auxiliary system, the closer it is combined with the theory of human kinematics and the higher the success rate of lower limb rehabilitation [2, 3]. is restricts the implementation of the rehabilitation plan
With the rapid development of industrial technology, advanced science and technology are introduced into rehabilitation training, and a wearable rehabilitation robot system is formed by combining robotics, mechatronics, biological rehabilitation, intelligent control, information fusion, and rehabilitation medicine theories [5]. e rehabilitation robot system is mainly composed of four parts: the perception system, the control system, the mechanical mechanism, and the power supply system. e perception system acquires the current motion mode, determines the wearer’s motion intention, and provides a decision signal to the control system

Summary

Research Article

Health Index Monitoring of Sports Injury Rehabilitation Training Based on Wearable Sensors. In order to design the perception system of the lower limb wearable rehabilitation robot, this study established the kinematics theoretical model of human lower limb and conducted the kinematics analysis of human body. By using the dynamic attitude analysis system, combined with the human body mark points, the position data of human body mark points in the process of standing up, sitting up, walking, stepping up, and squatting were collected. E results show that the angle of the hip joint changes regularly between 0° and 37° and the angle of the knee joint changes regularly between 0° and 70°during the standing process, which is consistent with the angle change trajectory collected by the dynamic attitude analysis system. E angle trajectories of the hip and knee joints measured by the absolute angle sensor are the same as those obtained by the dynamic attitude analysis system. Combined with the movement mechanism of human lower limbs, the characteristics of human motion state transition are analyzed, and the perceptual algorithm for judging human motion intention is studied, so as to determine the wearer’s current posture, standing intention while sitting, walking intention while standing, moving intention, and stopping intention during walking. e results show that the angle of the hip joint changes regularly between 0° and 37° and the angle of the knee joint changes regularly between 0° and 70°during the standing process, which is consistent with the angle change trajectory collected by the dynamic attitude analysis system. e angle trajectories of the hip and knee joints measured by the absolute angle sensor are the same as those obtained by the dynamic attitude analysis system. 1.5 rad and 0.3 rad were selected as reasonable and effective thresholds for determining sitting and standing states

Introduction

Journal of Healthcare Engineering

Research Methods

Joint angle

Results