EEG alpha rhythm detection on a portable device

Abstract Portable EEG devices have a great potential to become efficient computer interfaces. However, a necessary step is to accurately describe the EEG signal in order to quantify brain rhythms. This study explored two signal analysis techniques, Matching Pursuit (MP) and Fast Fourier Transform (FFT), for differentiation between two states, eyes open (EO) and eyes closed (EC), through the detection of EEG alpha activity obtained from seven scalp regions, using a portable EEG device. Subjects were ten healthy male volunteers. MP results generally reproduced the results from FFT analysis, and all methods performed well on the occipital region. However, there was better state discrimination with MP atom number, and MP atom number was the only variable that reached statistical significance on all locations under study. When employing EEG alpha rhythm for EO vs. EC state discrimination, it may be useful to compute MP atom number, especially when extra-occipital acquisition is warranted.

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