Classification of electrocardiographic signals: a fuzzy pattern matching approach

Abstract

In this paper we will deal with the problem of classification and interpretation of electrocardiograms (ECG) in the presence of uncertain environment. The problem can be conveniently handled in a general framework of pattern recognition. Uncertainty that is evident there relates both to (i) a perception perspective established in the classification process as well as (ii) final class assignment. Due to this type of uncertainty which essentially derives from a lack of sharp boundaries (i.e. precise definitions) of the features of the signal and the partial class membership (that is characteristic for unclear, borderline cases) of individual signals a methodology of fuzzy set theory is appropriate. Within this framework it will be clarified how all perception properties concerning signal processing and its interpretation can be handled.