A knowledge-based approach to ECG interpretation using fuzzy logic

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