Abstract
This work proposes to design a fuzzy proportional-integral derivative (FPID) controller for dual-sensor cardiac pacemaker systems, which can automatically control the heart rate to accurately track a desired preset profile. The combination of fuzzy logic and conventional PID control approaches is adopted for the controller design based on dual-sensors. This controller offers good adaptation of the heart rate to the physiological needs of the patient under different states (rest and walk). Through comparing with the conventional fuzzy control algorithm, FPID provides a more suitable control strategy to determine a pacing rate in order to achieve a closer match between actual heart rate and a desired profile. To assist the heartbeat recovery, the stimuli with adjustable pacing rate is generated by the pacemaker according to the FPID controller, such actual heart rate may track the preset heart rate faithfully. Simulation results confirm that this proposed control design is effective for heartbeat recovery and maintenance. This study will be helpful not only for the analysis and treatment of bradycardias but also for improving the performance of medical devices.
Highlights
CARDIOVASCULAR diseases are major causes of morbidity and mortality in the developed countries
Through comparing with the conventional fuzzy control algorithm, fuzzy proportional-integral derivative (FPID) provides a more suitable control strategy to determine a pacing rate in order to achieve a closer match between actual heart rate and a desired profile
To assist the heartbeat recovery, the stimuli with adjustable pacing rate is generated by the pacemaker according to the FPID controller, such actual heart rate may track the preset heart rate faithfully
Summary
CARDIOVASCULAR diseases are major causes of morbidity and mortality in the developed countries. The QT interval sensor measures the interval between the pacing spike and the evoked T-wave of ECG signal to ensure the estimated state It provides some consequence of physiological change and metabolic demand during walk or other conditions. In this paper we propose, for the first time, the combination of input variables with scaling factor of a PID controller and the fuzzy control mechanism for the dual-sensor cardiac pacemaker systems in patients with bradycardias, in which activity and QT interval are employed as adaptive parameters. Against the conventional fuzzy control scheme, the proposed fuzzy PID (FPID) controller in a closed-loop system determines the optimal pacing rate, automatically regulate the heart rate (HR) to track a desired preset HR profile for each particular patient more accurately and offer an adaptive tuning mechanism. The last section presents conclusion and future research directions
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