基于黎曼几何的自然动作运动参数脑电解码研究  

Decoding hand movement kinematic information from electroencephalogram based on riemannian geometry

作　　者：王勇[1] 薛沐辉 徐宝国[1] 宋爱国[1] Wang Yong;Xue Muhui;Xu Baoguo;Song Aiguo(School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China)

机构地区：[1]东南大学仪器科学与工程学院,南京210096

出　　处：《仪器仪表学报》2022年第7期157-164,共8页Chinese Journal of Scientific Instrument

基　　金：江苏省前沿引领技术基础研究专项(BK20192004);国家自然科学基金项目(61673114);中央高校基本科研业务费专项资金(2242022k30056)项目资助。

摘　　要：本文基于黎曼几何分类算法,探索了使用运动相关皮层电位(MRCPs)解码3种自然抓握动作的运动学信息的可能性。本研究采集了9名受试者在执行指捏、掌握和旋拧动作(包括两种不同水平的速度和力)的脑电图信号。在进行信号的预处理之后,将信号转化到协方差空间输入到黎曼均值最小距离(MDRM)分类器,实现基于MRCPs的手部自然动作的运动参数模式的识别。对于3种动作的运动参数,实验结果表明,二分类的总平均结果可以达到89.24%,四分类结果可以达到75.28%。本文采用的黎曼框架新颖高效,为脑-机接口的MRCP分类提供了新思路,同时本研究对于精细而自然地控制神经假体或者其他康复设备具有重要意义,这将大大提高运动障碍用户的认可度。Based on the Riemann geometric classification algorithm, we explore the possibility of decoding kinematic information of three natural reach-and-execute actions using movement-related cortical potentials(MRCPs). EEG signals are collected from 9 healthy subjects during the execution of pinch, palmar and precision disk rotation actions that involve two levels of speeds and forces. After preprocessing, MRCPs signals are transformed into covariance space and input into minimum distance to riemannian mean(MDRM) classifier. In this way, we successfully decode the movement parameters of natural hand movements based on MRCPs. For the kinematic parameters of three hand movement, we show that the grand average result of binary classification could reach 89.24%, and the result of multi-classification could reach 75.28%. The riemannian framework adopted in this article is novel and efficient, which provides a new way for MRCPs classification of brain-computer interface. Meanwhile, this study is of great importance for controlling neuroprosthesis or other rehabilitation devices in a fine and natural way, which could drastically increase the acceptance of motor impaired users.

关 键 词：脑-机接口 黎曼几何 手部自然抓握解码 运动学信息 运动相关电位 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TH-39[自动化与计算机技术—计算机科学与技术]