临床神经外科杂志2024，Vol.21Issue(4)：384-388,395,6.DOI:10.3969/j.issn.1672-7770.2024.04.005
一种基于手部精细运动分类的脑机接口方法研究
Study on a brain computer interface based on decoding of precise hand movements
摘要
Abstract
Objective To explore a motor-related brain computer interface(BCI)technology based on the decoding of six precise hand movements.Methods Based on the analysis of the mechanisms and response characteristics of six common types of fine motor electroencephalography(EEG)in the hand,a BCI paradigm for fine motor execution was designed.A motion related EEG signal decoding model based on convolutional neural networks was implemented,and a BCI system based on fine motor was built.Six types of fine motor gesture EEG signals from eight healthy subjects and two patients with significant motor dysfunction due to lesions involving the parietal lobe were classified.Results The classification accuracy of EEG signals in 10 subjects under the BCI system based on fine hand movements was(79.20±6.05)%.Conclusions The BCI method based on decoding six types of fine hand movements has certain effectiveness and generalization ability.关键词
精细运动/脑机接口/脑电信号/解码方法Key words
precise hand movement/brain computer interface/EEG/decoding method分类
医药卫生引用本文复制引用
李睿,刘宇琪,刘卫平,兀瑞,白端阳,杨东,张俊峰,赵杰..一种基于手部精细运动分类的脑机接口方法研究[J].临床神经外科杂志,2024,21(4):384-388,395,6.基金项目
西安市人民医院(西安市第四医院)科研孵化基金立项项目[2022BSH01(BH-1)] （西安市第四医院）
陕西省教育厅专项科研计划项目(22JK0471) （22JK0471）
