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

Abstract

Implantable cardiac pacemaker is a standard medical device totreat heart rhythm disorders. In this paper, a new adaptivebackstepping controller is developed to enhance the performanceof dual-sensor pacemakers for regulating the heart rate, based onradial basis function neural networks. The robust design ofadaptive backstepping controller using Lyapunov functions allowsguaranteeing the stability and performance of the rate-adaptivepacing system for accurately accomplishing the heart rateregulation at different preset values. This developed controlsystem has been retrospectively tested on six datasets of twopatients 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 showedthat the performance of developed backstepping controller issuperior to other pacemaker controllers in the previous studies.