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The paper addresses the problem of automatic sleep classification. A special effort is made to find a method of extracting reasonable descriptions of the individual sleep stages from sample measurements of EGG, EMG, EOG, etc., and from a classification of these measurements provided by an expert. The method should satisfy three requirements: classification accuracy, interpretability of the results, and the ability to select the relevant and discard the irrelevant variables. The solution suggested in this paper consists of a combination of the subsymbolic algorithm LVQ with the symbolic decision tree generator ID3. Results demonstrating the feasibility and utility of our approach are also presented.

biomedizinische technik

Towards Automated Sleep Classification in Infants Using Symbolic and Subsymbolic Approaches - Automatische Schlafklassifikation bei Säuglingen mit Hilfe von symbolischen und subsymbolischen Methoden