Proceedings of the Korean Information Science Society Conference (한국정보과학회:학술대회논문집)
- 2003.10b
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- Pages.739-741
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- 2003
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- 1598-5164(pISSN)
ICA＋OPCA for Artifact-Robust Classification of EEG
ICA＋OPCA를 이용한 잡음에 강인한 뇌파 분류
- Park, Sungcheol (Department of Computer Science, POSTECH) ;
- Lee, Hyekyoung (Department of Computer Science, POSTECH) ;
- Park, Seungjin (Department of Computer Science, POSTECH)
- Published : 2003.10.01
Abstract
Electroencephalogram (EEG)-based brain computer interface (BCI) provides a new communication channel between human brain and computer. EEG is very noisy data and contains artifacts, thus the extraction of features that are robust to noise and artifacts is important. In this paper we present a method with employ both independent component analysis (ICA) and oriented principal component analysis (OPCA) for artifact-robust feature extraction.
Keywords