{"title":"Novel BCI classification method using cross-channel-region CSP features","authors":"Yongkoo Park, Wonzoo Chung","doi":"10.1109/IWW-BCI.2018.8311528","DOIUrl":null,"url":null,"abstract":"In this paper, we explore locally generated cross-channel-region CSP features to improve motor imagery classification in EEG-based BCIs. We set several clustered sub-channel regions covering the entire measured channels and extract CSP features by cross-combining the sub-channel regions with each single channel. The features generated by this cross-channel-region combinations have regional information on sensor space for motor imagery and can be used to improve classification accuracy when fed to LS-SVM classifier. The performance improvement of the proposed algorithm is verified by simulations.","PeriodicalId":6537,"journal":{"name":"2018 6th International Conference on Brain-Computer Interface (BCI)","volume":"143 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 6th International Conference on Brain-Computer Interface (BCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWW-BCI.2018.8311528","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we explore locally generated cross-channel-region CSP features to improve motor imagery classification in EEG-based BCIs. We set several clustered sub-channel regions covering the entire measured channels and extract CSP features by cross-combining the sub-channel regions with each single channel. The features generated by this cross-channel-region combinations have regional information on sensor space for motor imagery and can be used to improve classification accuracy when fed to LS-SVM classifier. The performance improvement of the proposed algorithm is verified by simulations.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
