Literature DB >> 8957981

Fuzzy logic control of mechanical ventilation during anaesthesia.

J Schäublin1, M Derighetti, P Feigenwinter, S Petersen-Felix, A M Zbinden.   

Abstract

We have examined a new approach, using fuzzy logic, to the closed-loop feedback control of mechanical ventilation during general anaesthesia. This control system automatically adjusts ventilatory frequency (f) and tidal volume (VT) in order to achieve and maintain the end-tidal carbon dioxide fraction (FE'CO2) at a desired level (set-point). The controller attempts to minimize the deviation of both f and VT per kg body weight from 10 bpm and 10 ml kg-1, respectively, and to maintain the plateau airway pressure within suitable limits. In 30 patients, undergoing various surgical procedures, the fuzzy control mode was compared with human ventilation control. For a set-point of FE'CO2 = 4.5 vol% and during measurement periods of 20 min, accuracy, stability and breathing pattern did not differ significantly between fuzzy logic and manual ventilation control. After step-changes in the set-point of FE'CO2 from 4.5 to 5.5 vol% and vice versa, overshoot and rise time did not differ significantly between the two control modes. We conclude that to achieve and maintain a desired FE'CO2 during routine anaesthesia, fuzzy logic feedback control of mechanical ventilation is a reliable and safe mode of control.

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Year:  1996        PMID: 8957981     DOI: 10.1093/bja/77.5.636

Source DB:  PubMed          Journal:  Br J Anaesth        ISSN: 0007-0912            Impact factor:   9.166


  9 in total

Review 1.  Automatic control of mechanical ventilation. Part 1: theory and history of the technology.

Authors:  Fleur T Tehrani
Journal:  J Clin Monit Comput       Date:  2008-11-16       Impact factor: 2.502

2.  Operationalization of clinical practice guidelines using fuzzy logic.

Authors:  J C Liu; R N Shiffman
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

3.  Automated mechanical ventilation: adapting decision making to different disease states.

Authors:  S Lozano-Zahonero; D Gottlieb; C Haberthür; J Guttmann; K Möller
Journal:  Med Biol Eng Comput       Date:  2010-11-11       Impact factor: 2.602

4.  A dual closed-loop control system for mechanical ventilation.

Authors:  Fleur Tehrani; Mark Rogers; Takkin Lo; Thomas Malinowski; Samuel Afuwape; Michael Lum; Brett Grundl; Michael Terry
Journal:  J Clin Monit Comput       Date:  2004-04       Impact factor: 2.502

Review 5.  Automatic control of mechanical ventilation. Part 2: the existing techniques and future trends.

Authors:  Fleur T Tehrani
Journal:  J Clin Monit Comput       Date:  2008-11-20       Impact factor: 2.502

Review 6.  Fuzzy logic and decision-making in anaesthetics.

Authors:  Paul Grant; Ole Naesh
Journal:  J R Soc Med       Date:  2005-01       Impact factor: 18.000

7.  A Comparative Data-Based Modeling Study on Respiratory CO2 Gas Exchange during Mechanical Ventilation.

Authors:  Chang-Sei Kim; J Mark Ansermino; Jin-Oh Hahn
Journal:  Front Bioeng Biotechnol       Date:  2016-02-03

8.  Adaptive Fuzzy Sliding Mode Control of a Pressure-Controlled Artificial Ventilator.

Authors:  Ibrahim M Mehedi; Heidir S M Shah; Ubaid M Al-Saggaf; Rachid Mansouri; Maamar Bettayeb
Journal:  J Healthc Eng       Date:  2021-06-23       Impact factor: 2.682

Review 9.  The dawn of physiological closed-loop ventilation-a review.

Authors:  Philip von Platen; Anake Pomprapa; Burkhard Lachmann; Steffen Leonhardt
Journal:  Crit Care       Date:  2020-03-29       Impact factor: 9.097

  9 in total

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