A KNOWLEDGE-BASED APPROACH TO ECG INTERPRETATION USING FUZZY-LOGIC

A rule-based expert system which uses generalized modus ponens (GMP) f rom fuzzy logic as a rule of inference is described here for classific ation of abnormalities related to rhythm disorder in the human heart, through interpretation of the patient's electrocardiographic (EGG) pat terns. Application of GMP makes diagnosis of a wide range of variation s in the input ECG patterns possible even if they differ from the patt erns defined in the preconditions of the rules of the rulebase. The wo rk shows how fuzzy logic with suitably drawn possibility distributions of variables of cardiological domain plays a significant role in maki ng the expert system sensitive to finer variations of input ECG patter ns, which are very common in bioelectric signals, without enhancing th e size of the rulebase.