Rehabilitation Assessment Of Hemiplegia Patients Based On Wearable Intelligent Devices

The rehabilitation training for walking function is an important part of hemiplegia rehabilitation treatment,in which the objective analysis of the gait characteristics of patients is the basis for the development of rehabilitation training plan.However,in clinical practice,descriptive assessment methods are commonly used to conduct gait analysis,which mainly rely on motor function scales and experience of rehabilitation physicians.This method has poor objectivity and is difficult to accurately quantify patients’ motor characteristics.Therefore,objective and quantitative motion analysis techniques are urgently needed to evaluate the disease degree and rehabilitation process of hemiplegia patients.Recent advances in wearable sensor technology,especially the development of inertial sensors based on Micro-ElectroMechanical Systems(MEMS),have promoted their application in the field of medical rehabilitation.Wearable intelligent devices can obtain objective and quantitative human motion signals,which can provide a scientific basis for the formulation of treatment plans and evaluation of rehabilitation effects,and help improve the quality and efficiency of medical services.In this paper,a complete set of quantitative evaluation scheme is designed by using wearable intelligent devices.The main research contents include the following two aspects:(1)Calculation of spatial and temporal parameters of gait: based on MEMS inertial sensor nodes,the motion model of human feet and the whole lower limb is constructed,and the time phase parameters,foot motion parameters and lower limb joint angles are obtained.Through the adaptive peak detection algorithm,the four gait phases in walking movement are divided,and the algorithm can be improved to effectively divide the abnormal gait of patients.Based on two inertial sensor nodes,the motion of the feet is analyzed,and the information of posture,velocity and position of the feet is extracted.Based on seven inertial sensor nodes,the motion of the whole lower limb is captured and the motion state of the lower limb is reconstructed in real time.(2)Quantification of gait characteristics: through statistical analysis of healthy control group and hemiplegia patients,the degree of abnormal gait of patients is evaluated from three perspectives of symmetry,variability and stability.The symmetry of gait is evaluated by the characteristic of gait in time domain and space domain and its symmetry index.The variability of gait is evaluated by the periodic variation of gait parameters and its coefficient of variation.The stability of gait is evaluated according to the stability index,phase portrait and time series sample entropy of knee and ankle angles.In order to verify the effectiveness of the quantitative assessment method in the evaluation of abnormal gait,two sets of comparative experiments are designed.The rehabilitation of hemiplegia patients in different treatment stages is evaluated and contrastively analyzed,and it is verified that the evaluation results of the quantitative evaluation method proposed in this paper are consistent with the scale scores given by rehabilitation physicians.The experimental results indicate the effectiveness of the rehabilitation evaluation method based on wearable intelligent devices proposed in this paper.