Active triggering control of pneumatic rehabilitation gloves based on surface electromyography sensors.

ABSTRACT: The portable and inexpensive hand rehabilitation robot has become a practical rehabilitation device for patients with hand dysfunction. A pneumatic rehabilitation glove with an active trigger control system is proposed, which is based on surface electromyography (sEMG) signals. It can trigger the hand movement based on the patient's hand movement trend, which may improve the enthusiasm and efficiency of patient training. Firstly, analysis of sEMG sensor installation position on human's arm and signal acquisition process were carried out. Then, according to the statistical law, three optimal eigenvalues of sEMG signals were selected as the follow-up neural network classification input. Using the back propagation (BP) neural network, the classifier of hand movement is established. Moreover,

SUBMITTER: Feng Y 

PROVIDER: S-EPMC8064233 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature