Signal Processing of Finger Rehabilitation Therapy Based on sEMG
Finger function is particularly important in daily life,especially in some grasping and some fine movements,which has a non-negligible impact on the quality of daily life.Currently,the clinical treatment model for finger function rehabilitation mainly relies on auxiliary device rehabilitation,which can be rather monotonous.This article proposes a method to collect surface electromyography signals(sEMG)to enable patients with impaired finger function to be freed from the existing boring treatment methods,and at the same time,it is more conducive to the recovery of other functions such as nervous system function.The public dataset of EMG signals was used to pre-process the original EMG signals,and the correctness of the preprocessing was verified by MATLAB simulation.The feasibility of using the current EMG sensor for motor intention analysis was verified by collecting the patient's EMG signals in clinical experiments.
surface electromyography signalmotor intent analysisEMG signal preprocessingMATLAB
NETL
NSTL
万方数据
