Title :
Automatic Analysis of Sleep Electroencephalograms by Hybrid Computation
Author :
Smith, Jack R. ; Negin, Michael ; Nevis, Arnold H.
Author_Institution :
Department of Electrical Engineering, University of Florida, Gainesville, Fla.
Abstract :
An automated sleep electroencephalogram (EEG) analyzer has been designed and tested in an effort to eliminate tedious and variable human interpretation of experimental EEG data. Data is presented to a hybrid computer from EEG tapes recorded during experimental studies in a human sleep laboratory. Special analog filters are used to identify specific transient waveforms in the EEG. Bandpass filters are used to detect the rhythmical waveforms. The outputs of these filters are then processed by digital logic circuitry, whose algorithms emulate the rules used by human readers quantitating the level of sleep each minute according to the EEG pattem. Preliminary results give 89-percent correlation with a minute-by-minute comparison to the human evaluation of the same test EEG.
Keywords :
Band pass filters; Electroencephalography; Graph theory; Humans; Iterative methods; Logic circuits; Machinery; Pattern analysis; Pattern classification; Sleep;
Journal_Title :
Systems Science and Cybernetics, IEEE Transactions on
DOI :
10.1109/TSSC.1969.300220