Computer quantification of electroencephalographic data recorded from renal patients

Computer quantification of EEG records recorded from patients with renal disease reveals a slowing of the EEG correlated with deterioration of the patient's clinical condition. Electroencephalographic records were analyzed (1) by time averaged autocorrelation and subsequent Fourier transformation and (2) by generation of compressed spectra arrays (CSA). Quantification of the CSA provided estimates of the mean and variance of the percent power in selected frequency bandwidths in the EEG. This quantification has proved quite useful in the detection of slowing in EEG records.