eConHand: A Wearable Brain-Computer Interface System for Stroke Rehabilitation

被引：0

作者：

Qin, Zhun ^{[1
]}

Xu, Yao ^{[1
]}

Shu, Xiaokang ^{[1
]}

Hua, Lei ^{[1
]}

Sheng, Xinjun ^{[1
]}

Zhu, Xiangyang ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, 800 Dongchuan Rd, Shanghai, Peoples R China

来源：

2019 9TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER) | 2019年

基金：

美国国家科学基金会;

关键词：

MOTOR IMAGERY;

D O I：

10.1109/ner.2019.8716940

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Brain-Computer Interface (BCI) combined with assistive robots has been developed as a promising method for stroke rehabilitation. However, most of the current studies are based on complex system setup, expensive and bulky devices. In this work, we designed a wearable Electroencephalography(EEG)-based BCI system for hand function rehabilitation of the stroke. The system consists of a customized EEG cap, a small-sized commercial amplifer and a lightweight hand exoskeleton. In addition, visualized interface was designed for easy use. Six healthy subjects and two stroke patients were recruited to validate the safety and effectiveness of our proposed system. Up to 79.38% averaged online BCI classification accuracy was achieved. This study is a proof of concept, suggesting potential clinical applications in outpatient environments.

引用

页码：734 / 737

页数：4

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