Detection Methods of Brain Activity under Visual Cognitive Tasks Based on Information Processing of EEG Signals

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In this research project, we have performed studies on the development of detection method of brain activity under visual cognitive tasks based on information processing of electroencephalogram (EEG) signals and obtained following research results.1. EEG signal processing methodsWe have developed feature extraction and discrimination methods or EEG waves based on AR-model, Quasi ARMAX model and artificial neural networks. And it was also investigated that applied methods or wavelet analysis, blind separation analysis and event related de-synchronization analysis for EEG signals. An adaptive clustering method based on stochastic Newton method was developed and applied to EEG wave analysis. And it was confirmed that ERP (Event Related Potential) waves related to same kind of stimulus were belonged to some classes.2. Visual stimulating period and effect of eye blinkOptimal visual stimulating period were about 500msec for the discrimination or ERP signals, And eye blinks generated the noise component of EEG waves similar to ERP in shape. The effects of eye blink for the discrimination of EEG waves are under investigation.3. Discrimination of EEG waves under visual cognitive tasksThe effective electrode positions for the discrimination of ERP were Fz and Pz. Discrimination of stimuli (target or non-target) was tried based on EEG signal processing (AR model and statistical pattern recognition method). The accuracy based on regional EEG signals (spatial filtered signals) ws above 80%. These results suggest that human interface based on EEG signal processing would be feasible in near future.