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基于运动想象的脑-机接口关键问题及可能解决方案的综合评述

A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface.

机构信息

School of Fundamental Sciences, Massey University, 4410 Palmerston North, New Zealand.

出版信息

Sensors (Basel). 2021 Mar 20;21(6):2173. doi: 10.3390/s21062173.

DOI:10.3390/s21062173
PMID:33804611
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8003721/
Abstract

Motor imagery (MI) based brain-computer interface (BCI) aims to provide a means of communication through the utilization of neural activity generated due to kinesthetic imagination of limbs. Every year, a significant number of publications that are related to new improvements, challenges, and breakthrough in MI-BCI are made. This paper provides a comprehensive review of the electroencephalogram (EEG) based MI-BCI system. It describes the current state of the art in different stages of the MI-BCI (data acquisition, MI training, preprocessing, feature extraction, channel and feature selection, and classification) pipeline. Although MI-BCI research has been going for many years, this technology is mostly confined to controlled lab environments. We discuss recent developments and critical algorithmic issues in MI-based BCI for commercial deployment.

摘要

基于运动想象的脑-机接口（BCI）旨在通过利用因肢体运动想象而产生的神经活动来提供一种交流手段。每年都有大量与 MI-BCI 的新改进、挑战和突破相关的出版物。本文对基于脑电图（EEG）的 MI-BCI 系统进行了全面综述。它描述了 MI-BCI （数据采集、MI 训练、预处理、特征提取、通道和特征选择以及分类）管道不同阶段的当前技术水平。尽管 MI-BCI 研究已经进行了多年，但这项技术大多局限于受控的实验室环境。我们讨论了 MI 为基础的 BCI 在商业部署方面的最新进展和关键算法问题。

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