Fuzzy logic control of mechanical ventilation during anaesthesia.

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.

[1]  S. Kenny The Adelaide ventilation guide. , 1967, British journal of anaesthesia.

[2]  B. Ferris,et al.  Clinical use of a nomogram to estimate proper ventilation during artificial respiration. , 1954, The New England journal of medicine.

[3]  R. Fletcher Smoking, age and the arterial‐end‐tidal PCO2 difference during anaesthesia and controlled ventilation , 1987, Acta anaesthesiologica Scandinavica.

[4]  R. L. Coon,et al.  Systemic arterial blood pH servocontrol of mechanical ventilation. , 1978, Anesthesiology.

[5]  R. M. Peters,et al.  On-line digital analysis of respiratory mechanics and the automation of respirator control. , 1969, The Journal of thoracic and cardiovascular surgery.

[6]  Computer‐controlled optimization of positive end‐expiratory pressure , 1986, Critical care medicine.

[7]  D. A. Linkins Intelligent Control in Biomedicine , 1994 .

[8]  Dwayne R. Westenskow,et al.  A Microcomputer-Based Differential Lung Ventilation System , 1982, IEEE Transactions on Biomedical Engineering.

[9]  A. Zbinden,et al.  Arterial pressure control with isoflurane using fuzzy logic. , 1995, British journal of anaesthesia.

[10]  C Yoshimoto,et al.  An optimally controlled respirator. , 1971, IEEE transactions on bio-medical engineering.

[11]  M. Curatolo,et al.  Fuzzy logic control of inspired isoflurane and oxygen concentrations using minimal flow anaesthesia. , 1996, British journal of anaesthesia.

[12]  Louis C. Sheppard,et al.  Closed-Loop Control of an Anesthesia Delivery System: Development and Animal Testing , 1987, IEEE Transactions on Biomedical Engineering.

[13]  S. V. Ul'yanov,et al.  Dual control of the artificial ventilation process with use of a fuzzy controller in the feedback circuit , 1989 .

[14]  T. Lee,et al.  Tidal Volume, Lung Hyperinflation and Arterial Oxygenation during General Anaesthesia , 1993, Anaesthesia and intensive care.

[15]  D. Bogen,et al.  The Use of Computers for Controlling the Delivery of Anesthesia , 1992, Anesthesiology.

[16]  W. S. Jordan,et al.  MICROPROCESSOR CONTROL OF VENTILATION USING CARBON DIOXIDE PRODUCTION , 1979 .

[17]  A J Asbury,et al.  Fuzzy logic: new ways of thinking for anaesthesia. , 1995, British journal of anaesthesia.

[18]  G. A. Saxton,et al.  A servomechanism for automatic regulation of pulmonary ventilation. , 1957, Journal of applied physiology.

[19]  M. Frumin,et al.  A physiologically oriented artificial respirator which produces N20-02 anesthesia in man. , 1957, The Journal of laboratory and clinical medicine.

[20]  W. Heinrichs,et al.  An adaptive lung ventilation controller , 1994, IEEE Transactions on Biomedical Engineering.