Key result
Mamdani fuzzy controller cuts heart rate tracking error ~13% vs. FPID in simulated bradycardia.
Why the study?
Bradycardia, defined as heart rate less than 60 bpm, requires effective pacing systems to maintain adequate heart rate.
A Mamdani fuzzy controller can be designed and simulated in Matlab/Simulink to regulate pacing in a computational model of bradycardia.
Answers are grounded in this paper and cite their sources.
Simulation favors Mamdani fuzzy over FPID pacing control; leaves open clinical translation in bradycardia.
Cardiovascular disease is defined as a heart rate that is less than 60 bpm. Implantable cardiac devices such as pacemakers are widely used nowadays. In this paper, design and implementation of the heart model can be controlled to be the heart of a patient suffering from a decrease in heart rate (Bradycardia). A system is designed to sense and calculate the heart rate per minute and it is considered as an input to the controller. The design and implementation of Mamdani fuzzy controller to generate electric pulses that mimic the natural pacing system of the heart maintains an adequate heart rate by delivering controlled, rhythmic electrical stimuli to the chambers of the patient heart. The proposed controller is tested by using Matlab/Simulink program.
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Hamed et al. (2015) studied Bradycardia at rest. Mamdani Fuzzy Controller for Dual-Sensor Cardiac Pacemaker vs. FPID controller was evaluated on Root mean square error (rmse) of heart rate tracking. The proposed Mamdani fuzzy controller for a dual-sensor cardiac pacemaker achieved a lower root mean square error (1.0344) and steady-state error (2.41%) compared to an FPID controller in simulated patients with bradycardia at rest.
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