다채널 뇌파 분류를 위한 주성분 분석 기반 선형동적시스템

PCA-based Linear Dynamical Systems for Multichannel EEG Classification

EEG-based brain computer interface (BCI) provides a new communication channel between human brain and computer. The classification of EEG data is an important task in EEG-based BCI. In this paper we present methods which jointly employ principal component analysis (PCA) and linear dynamical system (LDS) modeling for the task of EEG classification. Experimental study for the classification of EEG data during imagination of a left or right hand movement confirms the validity of our proposed methods.