Detecting sensorimotor rhythms from the EEG signals using the independent component analysis and the coefficient of determination

Abstract

This paper proposes a method for highlighting the characteristics of sensorimotor rhythms (mu and beta). The electroencephalographic (EEG) data were recorded with 8 g.tec active electrodes by means of g.MOBIlab+ module. The EEG signals were filtered with a fifth order Butterworth band-pass filter between 0 and 30Hz and then the independent component analysis (ICA) was applied. The coefficient of determination (r2) has been computed for both situations, comparing the EEG spectra associated with each motor-imagery task with the spectra recorded in resting conditions. ICA and the coefficient of determination help us to demonstrate that the recorded data can be used to implement a brain computer interface (BCI) based on motor imagery tasks. Imagining left hand movement produces a desynchronization on CP4 and C4 electrodes in the right side of the scalp, while imagining right hand movement produces a desynchronization on CP3, C3 and P3 electrodes, on the left side of the brain.