Study of fuzzy systems with Sugeno and Mamdani-type fuzzy inference systems for determination of heartbeat cases on Electrocardiogram (ECG) signals

摘要

This paper discusses the suitability of implementing Sugeno- and Mamdani-type FISs for heartbeat case determination based on the Electrocardiogram (ECG) signals. The heartbeat cases are Normal Sinus Rhythm (NORM), Left Bundle Branch Block (LBBB), Right Bundle Branch Block (RBBB), Ventricular Premature Contractions (VPC) and Atrial Premature Contractions (APC). Overall, fuzzy system with Sugeno-type FIS was developed based on the FL method used in a paper. System modifications were carried out to create an alternative system for the application, implemented using Mamdani-type FIS. Both systems were verified with 3000 sets of random data for systems' performance comparison. Sugeno's system sensitivities in determining each heartbeat case are 100%, which leads to a TCA value of 100%, whereas in Mamdani's system, the sensitivities are all 100%, except for NORM heartbeat case which is 99.8% and thus TCA value is 99.9667%. It is also found that the Sugeno's system processing time is always less compared to Mamdani's system.