Blood Pressure Control by Deterministic Learning Based Fuzzy Logic Control
Bharat Singh1, Shabana Urooj2
1Bharat Singh, Department of Electrical Engineering, Gautam Buddha University, Greater Noida (U.P), India.
2Shabana Urooj Department of Electrical Engineering, Gautam Buddha University, Greater Noida (U.P), India.
Manuscript received on 18 February 2019 | Revised Manuscript received on 27 February 2019 | Manuscript published on 28 February 2019 | PP: 6-10 | Volume-8 Issue-3, February 2019 | Retrieval Number: B5543128218/19©BEIESP
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Abstract: Automatic control of blood pressure after cardiac operation of patient is wanted in favor of enhanced patient concern; it decreases work of personnel and expenses. Automation of medical drug infusion for controlling of mean arterial pressure (MAP) is extremely advantageous in much clinical function. An assimilating self-tuning control approach for the regulation of mean arterial pressure by infusing sodium nitroprusside is discussed. This paper focuses on omnipresent and verified FUZZY controllers based on reinforcement learning for arterial blood pressure control. The major problem is patient’s sensitivity in different condition although is same condition at different time. To extract the patient’s parameter reinforcement learning approach is proposed and verified. Complete & convenient model of hypertensive patient is effectively developed and processed; with drug response model depiction. Intend and execution of such control arrangement will be controlled using FUZZY logic controllers and for parameter extraction deterministic learning is used. MATLAB Simulation of the designed system models are done for revelation..
Keywords: Drug Delivery system, Deterministic Learning, Fuzzy Inference System, Mean Arterial Pressure
Scope of the Article: Fuzzy Logic