The efficient feature extraction from multichannel working memory task EEG signals is a major component for the cognitive state classification. In this study, four types of features including P300 peak latency, P300 peak amplitude, RMS, and theta frequency band power were chosen. They are classical, quantitative ERP measures that are commonly used in this field [14]. In particular, we extracted theta frequency band data of working memory task EEG signals through the wavelet packet transform (WPT) decomposition (4 levels) with the wavelet basis db4 and then calculated the energy spectrum.
