Abstract
The brain–computer interface P300 speller is aimed to help those patients unable to activate muscles to spell words by utilizing their brain activity. However, a problem associated with the use of this brain–computer interface paradigm is the generation mechanics of P300 related to responses to visual stimuli. Herein, we investigated the event-related potential (ERP) response for the P300-based brain–computer interface speller. A signal preprocessing method integrated coherent average, principal component analysis (PCA) and independent component analysis (ICA) to reduce the dimensions and noise in the raw data. The time–frequency analysis was based on wavelet and two characteristic parameters of event-related spectral perturbation (ERSP) and inter-trial coherence (ITC) were computed to indicate the evoked response (time-locked) and phase reset (phase-locked) activity, respectively. Results demonstrated that the proposed method was valid for the time-locked and phase-locked feature extraction and both the evoked response and phase reset contributed to the genesis of the P300 signal. These electrophysiological responses characteristics of ERPs would be used for BCI P300 speller design and its signal processing strategies.
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