Abstract

This work proposes methods to detect sleep spindles in the electroencephalographic activity, rapid eye movements (REM) in the electrooculographic activity, and chin muscle tone in the electromyographic activity in digital polysomnographic recordings. This is a first step in the design of an Expert System for automatic classification of sleep stages in normal infants.