Foot movement onset detection in self-paced BCIs using sparse representation based classifier

Self-paced BCI systems are more natural for real-life applications since these systems allow the user to control the system when desired. Detection of event periods in continuous EEG signal is one of the most important challenges in designing self-paced BCIs. In this paper, the Event related synchronization (ERS) is extracted from idle EEG signal using fractal dimensions in frequency range from 6 to 36 Hz and sparse representation based classifier. Our proposed method applied on EEG signal recorded during executing foot movement in 7 subjects. The average true positive rate and false positive rate equal to 90% and 5% were achieved.