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

被引：0

作者：

Tang, Rongnian ^{[1
]}

Xiao, Songyuan ^{[1
]}

Xie, Xiaofeng ^{[1
]}

Hou, Yao ^{[1
]}

Xie, Hongnan ^{[1
]}

Zhao, Xiaokang ^{[2
]}

Xu, Gaodi ^{[2
]}

机构：

[1] Hainan Univ, Mech & Elect Engn Coll, Haikou 570228, Hainan, Peoples R China

[2] Hainan Assoc Artificial Intelligence, Haikou 571158, Hainan, Peoples R China

来源：

INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS | 2024年 / 19卷 / 04期

基金：

中国国家自然科学基金;

关键词：

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

D O I：

10.1504/IJCSM.2024.139080

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页码：318 / 326

页数：10

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