Single-trial EEG analysis using similarity measure

Article type: Research Article

Authors: Hsu, Wei-Yen^{a; b}

Affiliations: [a] Department of Information Management, National Chung Cheng University, 168 University Rd. Sec. 1, Min-Hsiung Township, Chiayi County 621, Taiwan | [b] 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: [email protected], [email protected]

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.

Keywords: Electroencephalography (EEG), similarity measure, time–frequency representation, brain–computer interface (BCI)

DOI: 10.3233/BME-151554

Journal: Bio-Medical Materials and Engineering, vol. 26, no. 3-4, pp. 161-168, 2015