Real-Time CANFIS and ANFIS Based Pacemaker Controller Design and Analysis
Publish place: Signal Processing and Renewable Energy، Vol: 6، Issue: 3
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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JR_SPRE-6-3_006
تاریخ نمایه سازی: 11 مهر 1401
Abstract:
This paper describes ANFIS introduced by R. Jang et al. ANFIS actually is an offline method in fuzzy control systems. First, a fuzzy file called FIS (Fuzzy Inference System) is designed that relates the input and output of the system by membership functions that are optimized during the learning process. Input and output learning data are given to the ANFIS (MATLAB command line or ANFSI utility) and the output file is used to test or predict new input data. We can then construct a SIMULINK file to simulate the control system. This simulation is not real-time and if the environmental or input conditions are changed, the output will be altered because the FIS file is fixed and not adapted to input variations. The library of online ANFIS and CANFIS introduced does not have that problem and easily learns the online training data and then can mitigate the output in real-time. To avoid the unsuitable patient data itself as training data, we should use a healthy person ECG (heart rate) data in memory to train our fuzzy system and then switch the input data from healthy data to the patient original heart rate as input data. If the heartbeat falls below (۶۰ bpm that is called Bradycardia) or exceeds (۱۰۰bpm that is called Tachycardia) from a predetermined value. The online controller will switch the controller to healthy data and will stimulate heart muscles at a right beat rate (۷۰-۷۵ bpm). To distinguish tachycardia from body natural states like running, practicing, walking, sleeping and resting, MEMS accelerometer and in some situations, gyros are used. The Bode diagram stability shows gain and phase margin as follows: GM (dB)= ۴۲.۱ and PM (deg) = ۱۰۰. FIS file is saved after an acceptable rms error (۰.۳۸). The simulation results of unity step input response (Rise time, settling time, overshoot) will be demonstrated in chapter ۴. The overshoot was less than ۲ percent and rise time of ۲ seconds with settling time of less than ۲ seconds. The parameters have been shown for ۶۰ and ۷۲ and ۸۵ bpm.
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Authors
Asghar Dabiri Aghdam
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Nader Dabanloo
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Fereidoun Nooshiravan
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Keivan Maghooli
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran