计算机与现代化Issue(12)：19-23,5.DOI:10.3969/j.issn.1006-2475.2023.12.004
基于高效通道注意力模块的运动想象脑电识别
EEG Recognition of Motor Imagination Based on Efficiency Channel Attention Module
摘要
Abstract
The brain-computer interface technology based on motor imagination is helpful to the rehabilitation of patients with hand movement disorders,so it is widely used in the field of rehabilitation medicine.Aiming at the problem of poor classification of motor imagination-electroencephalogram(MI-EEG)due to its low signal-to-noise ratio in current motor imagination-electroencephalogram,in view of the ability of the attention module to focus on important features related to motor imagination classification tasks and ignore unimportant features,we propose a convolutional neural network based on the efficient channel at-tention(ECA)module for feature extraction and classification of left and right-handed MI-EEG.In order to facilitate the recogni-tion of EEG signals by convolutional neural network(CNN),this paper uses wavelet transform to convert the timing signals of C3 and C4 channels into two-dimensional time-frequency graphs,then designs a CNN structure and parameters based on ECA.Fi-nally,the proposed method is tested on EEG data set.The experimental results show that compared with CNN and the CNN method based on fusion convolution attention,the CNN method based on ECA can effectively improve the recognition accuracy of MI-EEG,indicating that the proposed method is effective in motor imagination EEG recognition.关键词
运动想象/脑电信号识别/小波变换/高效通道注意力模块/卷积神经网络/脑机接口Key words
motor imagination/EEG recognition/wavelet transform/efficiency channel attention module/convolutional neural network/brain-computer interface分类
医药卫生引用本文复制引用
周成诚,曾庆军,杨康,胡家铭,韩春伟..基于高效通道注意力模块的运动想象脑电识别[J].计算机与现代化,2023,(12):19-23,5.基金项目
国家自然科学基金资助项目(11574120) （11574120）
江苏省产业前瞻与共性关键技术项目(BE201803) （BE201803）
