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Adaptive Parameter Estimation-Based Drug Delivery System for Blood Pressure Regulation

  • Bharat Singh
  • Shabana Urooj
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 701)

Abstract

Controlled drug delivery system (DDS) is an electromechanical device that enables the injection of a therapeutic drug intravenously in the human body and improves its effectiveness and care by controlling the rate and time of drug release. Controlled operation of mean arterial blood pressure (MABP) and cardiac output (CO) is highly desired in clinical operation. Different methods have been proposed for controlling MABP; all methods have certain disadvantages according to patient model. In this paper, we have proposed blood pressure control using integral reinforcement learning-based fuzzy inference system (IRLFI) based on parameter estimation technique. To further increase the safety of the proposed method, a supervisory algorithm is implemented, which maintains the infusion rate within safety limit. MATLAB simulation depends the model of MABP, elucidate the ability of the suggested methodology in designing DDS and control postsurgical MABP.

Keywords

Drug delivery system Fuzzy inference system Mean arterial blood pressure Sodium nitroprusside Maximum a posteriori estimators 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Bharatividyapeeth’s College of EngineeringNew DelhiIndia
  2. 2.School of EngineeringGautam Buddha UniversityGreater NoidaIndia

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