Title: Analyse the brain imagine patterns under different functional electrical stimulation on the upper limb movement BCI system

Authors: Rongnian Tang; Songyuan Xiao; Xiaofeng Xie; Yao Hou; Hongnan Xie; Xiaokang Zhao; Gaodi Xu

Addresses: The Mechanical and Electrical Engineering College, Hainan University, Haikou, Hainan, 570228, China ' The Mechanical and Electrical Engineering College, Hainan University, Haikou, Hainan, 570228, China ' The Mechanical and Electrical Engineering College, Hainan University, Haikou, Hainan, 570228, China ' The Mechanical and Electrical Engineering College, Hainan University, Haikou, Hainan, 570228, China ' The Mechanical and Electrical Engineering College, Hainan University, Haikou, Hainan, 570228, China ' Hainan Association for Artificial Intelligence, Haikou, Hainan, 571158, China ' Hainan Association for Artificial Intelligence, Haikou, Hainan, 571158, China

Abstract: The brain computer interface (BCI) systems based on motor imagery was widely used for upper limb rehabilitation of stroke patients. Functional electrical stimulation (FES) can generate artificial muscle contraction by sending electrical pulses to limbs to achieve the rehabilitation. Previous work mainly focused on the qualitative analysis of feedback, rarely on the quantitative analysis of feedback with FES. In this paper, we quantitatively analysed the effect of FES on motor imagery. By analysing the classification performance under different FES values from the in-house experimental dataset, we can infer that the greater the intensity of FES, the greater the enhancement of the classification effect of motor imagery task.

Keywords: BCI; brain computer interface; motor imagery; EEG signal; FES; functional electrical stimulation; rehabilitation.

DOI: 10.1504/IJCSM.2024.139080

International Journal of Computing Science and Mathematics, 2024 Vol.19 No.4, pp.318 - 326

Received: 30 Nov 2022
Accepted: 27 Dec 2023
Published online: 12 Jun 2024 *

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