Adaptive Heart Rate Regulation Using Implantable Pacemaker with Artificial Neural Network-Based Backstepping Controller

Karar, Mohamed Esmail

doi:10.21608/mjeer.2018.63254

Adaptive Heart Rate Regulation Using Implantable Pacemaker with Artificial Neural Network-Based Backstepping Controller

Document Type : Original Article

Author

Mohamed Esmail Karar

Dept. of Industrial Elect. and Control Eng., Faculty of Elect. Eng., Menoufia University

10.21608/mjeer.2018.63254

Abstract

Implantable cardiac pacemaker is a standard medical device to
treat heart rhythm disorders. In this paper, a new adaptive
backstepping controller is developed to enhance the performance
of dual-sensor pacemakers for regulating the heart rate, based on
radial basis function neural networks. The robust design of
adaptive backstepping controller using Lyapunov functions allows
guaranteeing the stability and performance of the rate-adaptive
pacing system for accurately accomplishing the heart rate
regulation at different preset values. This developed control
system has been retrospectively tested on six datasets of two
patients with a pacemaker during three body activities of the rest,
walking, and exercising. The resulting root mean square error
(RMSE) and maximum error are less than 0.36 and 0.50 %,
respectively. In addition, comparative results of this study showed
that the performance of developed backstepping controller is
superior to other pacemaker controllers in the previous studies.

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