A new 2-class unilateral upper limb motor imagery tasks for stroke rehabilitation training

Banghua Yang; Jun Ma; Wenzheng Qiu; Yan Zhu; Xia Meng

Medicine in Novel Technology and Devices (Mar 2022)

A new 2-class unilateral upper limb motor imagery tasks for stroke rehabilitation training

Banghua Yang,
Jun Ma,
Wenzheng Qiu,
Yan Zhu,
Xia Meng

Affiliations

Banghua Yang: School of Mechatronic Engineering and Automation, School of Medicine, Research Center of Brain Computer Engineering, Shanghai University, Shanghai, 200444, China; Corresponding author. School of Mechatronic Engineering and Automation, School of Medicine, Research Center of Brain Computer Engineering, Shanghai University, 99 Shangda Road BaoShan District, Shanghai, 200444, PR China.
Jun Ma: School of Mechatronic Engineering and Automation, School of Medicine, Research Center of Brain Computer Engineering, Shanghai University, Shanghai, 200444, China
Wenzheng Qiu: School of Mechatronic Engineering and Automation, School of Medicine, Research Center of Brain Computer Engineering, Shanghai University, Shanghai, 200444, China
Yan Zhu: The Second Rehabilitation Hospital of Shanghai, Shanghai, 200441, China
Xia Meng: China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China

Journal volume & issue: Vol. 13
p. 100100

Abstract

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The rehabilitation training based on motor imagery brain-computer interface (MI-BCI) is considered to be an effective method. We designed a new 2-class unilateral upper limb motor imagery tasks. Data from 15 healthy subjects and 10 stoke patients are collected in the study. The results of event-related desynchronization/synchronization (ERD/ERS) and power spectral density (PSD) analysis showed the significant different features on health subjects and stroke patients. The improved 2-Conv-FBCNET is used to classify Electroencephalogram (EEG) signals and the accuracy is (health: 61.0%, stroke: 59.4%). The new two types of tasks provide a new training method for MI-BCI rehabilitation training system.

Published in Medicine in Novel Technology and Devices

ISSN: 2590-0935 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Medicine (General): Medical technology
Website: https://www.journals.elsevier.com/medicine-in-novel-technology-and-devices

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