Power and asymmetry ratio of spectral bands for mental task recognition

We use the power and asymmetry ratio of spectral bands to recognise mental tasks from electroencephalogram signals using a fuzzy ARTMAP neural network. Classical spectral analysis using the Wiener-Khintchine theorem and modem parametric spectral analysis using the autoregressive method are used to obtain these features. The highest classification results of 90% for a subject recognising two mental tasks validate the method.