Since electro-oculographic (EOG) activity during human sleep appears to be of medical diagnostic and prognostic value, the vast amount of EOG data representative of even a single night's sleep warrants the development of automated pattern recognition and information extraction techniques. Such a technique for the analysis of sleep EOG rapid eye movement (REM) is presented in which the time of occurrence, area, height, duration and binocular symphrony for each REM are measured. This automated technique for sleep EOG analysis is currently used in the investigation of periodicities and values of REM parameters for normal subjects and in the differential diagnosis of affective disorders.
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