Literature DB >> 7729836

Multiple drug hemodynamic control by means of a supervisory-fuzzy rule-based adaptive control system: validation on a model.

C M Held1, R J Roy.   

Abstract

A control device that uses an expert system approach for a two input-two output system has been developed and evaluated using a mathematical model of the hemodynamic response of a dog. The two inputs are the infusion rates of two drugs: sodium nitroprusside (SNP) and dopamine (DPM). The two controlled variables are the mean arterial pressure and the cardiac output. The control structure is dual mode, i.e., it has two levels: a critical conditions (coarse) control mode and a noncritical conditions (fine) control mode. The system switches from one to the other when threshold conditions are met. Different "controller parameters sets"-including the values for the threshold conditions-can be given to the system which will lead to different controller outputs. Both control modes are rule-based, and supervisory capabilities are added to ensure adequate drug delivery. The noncritical control mode is a fuzzy logic controller. The system includes heuristic features typically considered by anesthesiologists, like waiting periods and the observance of a "forbidden dosage range" for DPM infusion when used as an inotrope. An adaptation algorithm copes with the wide range of sensitivities to SNP found among different individuals, as well as the time varying sensitivity frequently observed in a single patient. The control device is eventually tested on a nonlinear model, designed to mimic the conditions of congestive heart failure in a dog. The test runs show a highest overshoot of 3 mmHg with nominal SNP sensitivity. When tested with different simulated SNP sensitivities, the controller adaptation produces a faster response to lower sensitivities, and reduced oscillations to higher sensitivities. The simulations seem to show that the system is able to drive and adequately keep the two hemodynamic variables within prescribed limits.

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Year:  1995        PMID: 7729836     DOI: 10.1109/10.376130

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Automatic regulation of hemodynamic variables in acute heart failure by a multiple adaptive predictive controller based on neural networks.

Authors:  Koji Kashihara
Journal:  Ann Biomed Eng       Date:  2006-10-18       Impact factor: 3.934

2.  ASIC design of a digital fuzzy system on chip for medical diagnostic applications.

Authors:  Shubhajit Roy Chowdhury; Aniruddha Roy; Hiranmay Saha
Journal:  J Med Syst       Date:  2009-08-27       Impact factor: 4.460

3.  Modelling and multi-parametric control for delivery of anaesthetic agents.

Authors:  Pinky Dua; Vivek Dua; Efstratios N Pistikopoulos
Journal:  Med Biol Eng Comput       Date:  2010-04-20       Impact factor: 2.602

4.  Accuracy enhancement in a fuzzy expert decision making system through appropriate determination of membership functions and its application in a medical diagnostic decision making system.

Authors:  Suddhasattwa Das; Shubhajit Roy Chowdhury; Hiranmay Saha
Journal:  J Med Syst       Date:  2010-11-24       Impact factor: 4.460

5.  Multi-complexity measures of heart rate variability and the effect of vasopressor titration: a prospective cohort study of patients with septic shock.

Authors:  Samuel M Brown; Jeffrey Sorensen; Michael J Lanspa; Matthew T Rondina; Colin K Grissom; Sajid Shahul; V J Mathews
Journal:  BMC Infect Dis       Date:  2016-10-10       Impact factor: 3.090

6.  Norepinephrine weaning in septic shock patients by closed loop control based on fuzzy logic.

Authors:  Mehdi Merouani; Bruno Guignard; François Vincent; Stephen W Borron; Philippe Karoubi; Jean-Philippe Fosse; Yves Cohen; Christophe Clec'h; Eric Vicaut; Carole Marbeuf-Gueye; Frederic Lapostolle; Frederic Adnet
Journal:  Crit Care       Date:  2008-12-09       Impact factor: 9.097

  6 in total

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