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Design and processing of a novel algorithm using Anfis for new generation of cardiac pacemakers

机译：使用Anfis的新型算法用于新一代心脏起搏器的设计和处理

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This paper presents a new intelligent control algorithm using Anfis (Adaptive neuro fuzzy inference system) for new generation of Cardiac Pacemakers. Anfis uses both merits of Fuzzy and Neural networks (Learning and speed). Based on various states of body (rest, walking and exercising) and preprogramed states of patient (Sex, age, blood pressure) heart rate and amplitude of exciting pulses will be changed. A feedback from output ECG signal fed back and compared in Anfis controller. Anfis compared with other fuzzy control algorithms provides better control scheme for estimation and generation of pacing pulse parameters including rate and amplitude. Accelerometer sensors and HRV and GSR are used for stabilization of ECG signal during the three body states [1]. Old designs of pacemakers cannot solve problems but Fuzzy can do the job very fast and accurately. Anfis method designed externally regarding patient conditions and normal ECG signals data captured from a known database (based on age and sex of patient) then calculated in MATLAB (Simulink) and programmed directly or wirelessly by ultrasound signals (a novel proposed method). Previous researches [4-19-20] are based on fuzzy PID and fuzzy logic controller in patients with cardiovascular diseases. Anfis controller offers good adaptation of the heart rate and other ECG parameters to the physiological needs of patient.
机译：本文提出了一种使用Anfis（自适应神经模糊推理系统）的新型智能控制算法，用于新一代心脏起搏器。 Anfis同时使用了模糊和神经网络的优点（学习和速度）。根据身体的各种状态（休息，步行和运动）以及患者的预编程状态（性别，年龄，血压），心率和激发脉冲的幅度将发生变化。来自输出ECG信号的反馈被反馈并在Anfis控制器中进行比较。与其他模糊控制算法相比，Anfis提供了更好的控制方案，用于估计和生成包括速率和幅度在内的起搏脉冲参数。加速度传感器和HRV和GSR用于在三种身体状态下稳定心电信号[1]。旧的起搏器设计无法解决问题，但Fuzzy可以非常快速，准确地完成这项工作。 Anfis方法是根据患者状况和从已知数据库捕获的正常ECG信号数据（基于患者的年龄和性别）在外部进行设计的，然后在MATLAB（Simulink）中进行计算，并通过超声信号直接或无线编程（提出的一种新方法）。先前的研究[4-19-20]是基于模糊PID和模糊逻辑控制器的心血管疾病患者。 Anfis控制器可根据患者的生理需求很好地适应心率和其他ECG参数。

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