Clinical applications of spectral analysis and extraction of features from electroencephalograms with slow waves in adult patients

Abstract

A method is described for extracting from EEGs clinically relevant features, using a small computer. The basic principle is to compute the activity in different frequency bands (delta, theta, alpha, beta), using spectral analysis, and to study some of the relations between these activities. In patients with localized supratentorial brain lesions, the EEG usually presents localized slow waves and also decreased background activity (alpha and beta) in areas nearest to the lesion. A ration of the type (delta + theta)/(alpha + beta) should therefore act as a good indicator of the importance of the abnormality. This ration is improved by using an empirical type of discriminant analysis, applied to a group of normal subjects and to a group of patients. Using a 40 sec sample of the EEG, a concentrated report in the form of a visual, topographically organized display is issued on the computer graphic terminal after a few minutes of computation, reflecting the values of the feature for each of the 16 channels of EEG and some of the relations between channels. The readability of this display to a non-electroencephalographer is a useful feature, especially since it presents in a topographical arrangement clinically significant numerical features which can be apprehended at a glance and are not available to the interpreter of the EEG using the traditional visual inspection method.