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.
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