Modelling and multivariable control in anaesthesia using neural-fuzzy paradigms. Part I. Classification of depth of anaesthesia and development of a patient model.
OBJECTIVE
The first part of this research relates to two strands: classification of depth of anaesthesia (DOA) and the modelling of patient's vital signs.


METHODS
First, a fuzzy relational classifier was developed to classify a set of wavelet-extracted features from the auditory evoked potential (AEP) into different levels of DOA. Second, a hybrid patient model using Takagi-Sugeno Kang fuzzy models was developed. This model relates the heart rate, the systolic arterial pressure and the AEP features with the effect concentrations of the anaesthetic drug propofol and the analgesic drug remifentanil. The surgical stimulus effect was incorporated into the patient model using Mamdani fuzzy models.


RESULTS
The result of this study is a comprehensive patient model which predicts the effects of the above two drugs on DOA while monitoring several vital patient's signs.


CONCLUSIONS
This model will form the basis for the development of a multivariable closed-loop control algorithm which administers "optimally" the above two drugs simultaneously in the operating theatre during surgery.
Nunes
Catarina S
CS
Departamento de Matemática Aplicada, Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal.
Mahfouf
Mahdi
M
Linkens
Derek A
DA
Peacock
John E
JE
D000465:Algorithms; D018686:Anesthetics, Intravenous / Q000494:pharmacology*; D001794:Blood Pressure / Q000187:drug effects; D005072:Evoked Potentials, Auditory / Q000187:drug effects; D017143:Fuzzy Logic; D006339:Heart Rate / Q000187:drug effects; D006801:Humans; D008954:Models, Biological; D016571:Neural Networks, Computer; D010880:Piperidines / Q000494:pharmacology*; D015742:Propofol / Q000494:pharmacology*; D000077208:Remifentanil
D018686:Anesthetics, Intravenous; D010880:Piperidines; D000077208:Remifentanil; D015742:Propofol