By Topic

SADAP: a simulator for hierarchical fuzzy control of depth of anaesthesia

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Linkens, D.A. ; Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK ; Shieh, J.S. ; Peacock, J.E.

SADAP has been developed to simulate the administration of intravenous and analgesic drugs. It merges on-line measurements (such as systolic arterial pressure (SAP) and heart rate (HR)) and non-numerical clinical signs (such as sweating, lacrimation and pupil response) using anaesthetists' experience or self-organizing fuzzy logic control (SOFLC) algorithms to administer drugs into a patient. The hierarchical control architecture includes five parts which are: inferring DOA, drug controller, deciding the sensitivity of patient, fentanyl supplementation, and recovery time. It has been developed to predict drug profiles, control the drug levels, and assess recovery time during anaesthesia. Linguistic rules and fuzzy set theory have been used to model a patient during induction and maintenance stages. Successful results have given confidence to perform on-line clinical trials in operating theatre. In parallel research, the same generic architecture has been successfully demonstrated for inhalational anaesthesia using the gaseous drug isoflurane

Published in:

Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,

Date of Conference:

18-21 Dec 1994