现代信息科技2024，Vol.8Issue(21)：96-101,6.DOI:10.19850/j.cnki.2096-4706.2024.21.019
基于最优频段选择的运动想象研究
Research on Motor Imagery Based on Optimal Frequency Band Selection
张光旭 1张晓丹1
作者信息
- 1. 西安工程大学 电子信息学院,陕西 西安 710048
- 折叠
摘要
Abstract
Electroencephalogram(EEG)signals consist of multiple frequency bands,with motor imagery primarily involving the mu and beta bands.When the required frequency bands are clearly defined,classification tasks can generally be performed smoothly.However,frequency band selection has not been a major focus of research.Thus,developing an application capable of screening the optimal frequency bands for classification tasks is particularly important.This research analyzes the classification performance of EEG data related to visual cue-based left-hand and right-hand motor imagery based on the BCI Competition IV dataset 2b.The experiments utilize a 10-fold cross-validation approach to evaluate the models,aiming to reduce randomness and provide stable performance metrics.This research applies two models of BP-CNN and AR-CNN,and compares them with a CNN model that extends the frequency bands within known ranges.Even within unknown frequency ranges,effective motor imagery recognition is achieved through precise frequency band selection and model optimization.It provides a theoretical foundation for brain-computer interface technology and offers significant reference value for future research in related fields.关键词
运动想象/脑机接口/频段选择/卷积神经网络Key words
motor imagery/brain-computer interface/frequency band selection/Convolutional Neural Networks分类
信息技术与安全科学引用本文复制引用
张光旭,张晓丹..基于最优频段选择的运动想象研究[J].现代信息科技,2024,8(21):96-101,6.
