Adaptive fuzzy modeling of the hypnotic process in anesthesia.

This paper addresses the problem of patient model synthesis in anesthesia. Recent advanced drug infusion mechanisms use a patient model to establish the proper drug dose. However, due to the inherent complexity and variability of the patient dynamics, difficulty obtaining a good model is high. In this paper, a method based on fuzzy logic and genetic algorithms is proposed as an alternative to standard compartmental models. The model uses a Mamdani type fuzzy inference system developed in a two-step procedure. First, an offline model is obtained using information from real patients. Then, an adaptive strategy that uses genetic algorithms is implemented. The validation of the modeling technique was done using real data obtained from real patients in the operating room. Results show that the proposed method based on artificial intelligence appears to be an improved alternative to existing compartmental methodologies.

Modelling propofol pharmacodynamics using BIS-guided anaesthesia.

Using Schnider's pharmacokinetic model, propofol pharmacodynamics were modelled during total intravenous anaesthesia. The method involved adjusting a pharmacokinetic/pharmacodynamic model according to data obtained from 42 patients having operative procedures with remifentanil analgesia. Parameters Ce50 and γ were estimated for induction and maintenance by analysing patients' bispectral index. The pharmacodynamic models were different for induction and maintenance. The mean (95% CI) Ce50 for induction and maintenance was Ce50 = 3.35 (2.79-3.91) mg.l(-1) and 2.23 (1.95-2.51) mg.l(-1) , respectively, with a higher concentration required to achieve the same effect during induction, even during remifentanil co-administration. During induction and maintenance, γ was 1.24 (1.44-2.00) and 1.58 (1.32-1.84), respectively. As γ is related to the concentration-effect slope, patient response is accentuated during maintenance compared with induction. The influence of sex and age on the model was analysed. Sex had no significant influence on the model, although a linear relation was found between age and Ce50 .

Design and implementation of a closed-loop control system for infusion of propofol guided by bispectral index (BIS).

BACKGROUND: This study describes the design of a hypnosis closed-loop control system with propofol. The controller used a proportional-integral (PI) algorithm with the bispectral index (BIS) as the feedback signal. Our hypothesis was that a PI closed-loop control could be applied in clinical practice safely keeping the BIS within a pre-determined target range. METHODS: The adjustment of the PI parameters was based on simulation. The procedure had three steps: obtaining a patient model using data from 12 patients, designing and adjusting the controller in simulation, and fine tuning the PI parameters in a pilot study (10 patients). The resulting controller was tested in 24 American Society of Anesthesiology (ASA) I-II patients. The controller directly decides the infusion rate of propofol, and no model is necessary in its online operation. The BIS target was set to 50. Remifentanil was used for analgesia. RESULTS: We evaluated the efficiency and safety of the automatic feedback system. It worked properly in all the patients. The median performance error was -1.62, and the median absolute performance error was 11.03. Average propofol-normalized consumption was 5.3 ± 1.8 mg/kg/h. Mean percentage of BIS in the range 40-60 was 83%. Mean time to open eyes was 8 ± 4 min. Time to extubation was 9 ± 5 min. Hemodynamic adverse event or intraoperative awareness were not recorded. CONCLUSIONS: The closed-loop system was able to maintain the BIS within an acceptable range of levels. The control of a propofol infusion guided by the BIS is feasible without hemodynamic instability in ASA I/II patients.