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In previous studies we have introduced a brain-computer interface (BCI) system based on movement related cortical potentials (MRCP). The performance of this system was shown to be significantly affected by the users’ attention state. In the current study, we analyzed MRCP features (low frequencies) and features extracted at higher frequencies to determine the effect of variations in user’s attention on EEG. Attention was modulated by a combination of auditory and visual stimuli that served as external distractors from the main task, which was a simple dorsiflexion. Time and frequency analysis was performed on EEG signals recorded from twenty-eight channels. The amplitude of the peak negativity and the slope of the negative deflection of the MRCP decreased and pre-movement variability increased with the distractors. Moreover, spectral analysis revealed an increment of theta power and alpha power due to attentional shifts. These results have implications for the design of real-life BCI systems, potentially allowing an increased robustness and adaptability with users’ conditions.

Detection of Attention alteration of BCI Users based on EEG Analysis