Sleep stage classification using fuzzy sets and machine learning techniques

Abstract The hypnogram is determined after a study of electrophysiological records. In this paper we present the Intelligent system for sleep stages classification (ISSSC). This system is divided into four different modules: the first processes the electrophysiological signals and determines its most relevant parameters; the second module establishes fuzzy rules that will be used during the classification process; the third module is an inference module, it implements a fuzzy model. Finally the system builds the patient's hypnogram and provides us different outputs. We present the classification results obtained from applying the systems to classify patients with different sleep disorders.