Adaptive Heart Rate Regulation Using Implantable Pacemaker with Artificial Neural Network-Based Backstepping Controller | ||||
Menoufia Journal of Electronic Engineering Research | ||||
Article 12, Volume 27, Issue 2, July 2018, Page 259-274 | ||||
Document Type: Original Article | ||||
DOI: 10.21608/mjeer.2018.63254 | ||||
View on SCiNiTO | ||||
Author | ||||
Mohamed Esmail Karar | ||||
Dept. of Industrial Elect. and Control Eng., Faculty of Elect. Eng., Menoufia University | ||||
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. | ||||
References | ||||
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