Automatic selection of frequency and time intervals for classification of EEG signals

A novel technique is presented for the automatic selection of time and frequency intervals to be used in feature extraction on multidimensional signals acquired by an electroencephalogram (EEG). This technique is completely automatic, adaptive (task independent), and does not require any specific prior domain knowledge. Experimental results obtained by integrating the proposed technique in a system for brain computer interface (BCI) confirm its effectiveness.