title: Single-trial EEG analysis using similarity measure.
abstract: Single-trial electroencephalogram (EEG) data are analyzed with similarity measure. Time-frequency representation is constructed from EEG signals. It is then weighted with t-statistics. Finally, the test data are discriminated with similarity measure. Compared with non-weighted version, the experimental results indicate that the proposed method obtains better results in classification accuracy.
authors.affiliation: Department of Information Management, National Chung Cheng University, 168 University Rd. Sec. 1, Min-Hsiung Township, Chiayi County 621, Taiwan.|Advanced Institute of Manufacturing with High-tech Innovations, National Chung Cheng University, 168 University Rd. Sec. 1, Min-Hsiung Township, Chiayi County 621, Taiwan. Tel.: +886 5 2720411, #34621;Fax: +886 5 2721501; E-mails: shenswy@gmail.com, shenswy@mis.ccu.edu.tw.
authors.forename: Wei-Yen
authors.initials: WY
authors.lastname: Hsu
mesh_terms: D001921:Brain / Q000648:ultrastructure; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface
keywords: Electroencephalography (EEG); brain–computer interface (BCI); similarity measure; time–frequency representation