Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum.

Spectrum and bispectral analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease patients and further applied to distinguish AD patients from the normal controls and indicate that all these features could differentiate AD patients with a maximum accuracy of 90.2%.