Literature DB >> 30588292

An optimized Mamdani FPD controller design of cardiac pacemaker.

Mohamed I Elnaggar1, Amira S Ashour1, Yanhui Guo2, Heba A El-Khobby1, Mustafa M Abd Elnaby1.   

Abstract

Cardiac pacemaker is a standard implantable medical electronic device for management and treatment of the heart rhythm disorders aiming to improved healthcare. Developing a new pacemaker based heart stimulation techniques has a vital role in preserving the patient's life. This target inspired the present work to design a new Mamdani fuzzy proportional-derivative (FPD) controller of a cardiac pacemaker, where Mamdani algorithm is the most common algorithm to deal with the human signals. The electrical pulses have closed features to the Sino atrial node pulses, which are delivered to the patient's heart chamber model using the FPD controller to regulate and recover a normal heart rate (HR) precisely. The FPD controller is considered an integration of conventional proportional-integral-derivative (PID) controller and the fuzzy techniques to realize precise, controlled and regulated HR that follows the desired set point. Furthermore, an optimization technique is used to determine the optimally tuned gains of the controller. The proposed model is designed, tested, and simulated along with tuning the controller gains using Matlab/Simulink software. The simulation results confirmed the impact of the proposed controller to achieve the optimal HR adaptation to the desired patient's physiological needs at rest compared to the existing PID, fuzzy and fuzzy PID control algorithms. The output response has a closed and regulated pacing rate with a rapid rise time of 0.5 s, the rapid settling time of 2 s, and very small error of 0.5% with overshooting of 0.4%.

Entities:  

Keywords:  Artificial pacemaker; Bradycardia; Fuzzy logic; Fuzzy proportional–integral–derivative; Heart rate; Proportional–integral–derivative

Year:  2018        PMID: 30588292      PMCID: PMC6261926          DOI: 10.1007/s13755-018-0063-z

Source DB:  PubMed          Journal:  Health Inf Sci Syst        ISSN: 2047-2501


  1 in total

1.  Guest Editorial: Special issue on "Application of artificial intelligence in health research".

Authors:  Siuly Siuly; Xiangliang Zhang
Journal:  Health Inf Sci Syst       Date:  2019-12-06
  1 in total

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