title: Fuzzy logic based anaesthesia monitoring systems for the detection of absolute hypovolaemia.
abstract: Anaesthesia monitoring involves critical diagnostic tasks carried out amongst lots of distractions. Computers are capable of handling large amounts of data at high speed and therefore decision support systems and expert systems are now capable of processing many signals simultaneously in real time. We have developed two fuzzy logic based anaesthesia monitoring systems; a real time smart anaesthesia alarm system (RT-SAAM) and fuzzy logic monitoring system-2 (FLMS-2), an updated version of FLMS for the detection of absolute hypovolaemia. This paper presents the design aspects of these two systems which employ fuzzy logic techniques to detect absolute hypovolaemia, and compares their performances in terms of usability and acceptability. The interpretation of these two systems of absolute hypovolaemia was compared with clinicians' assessments using Kappa analysis, RT-SAAM K=0.62, FLMS-2 K=0.75; an improvement in performance by FLMS-2.
authors.affiliation: Department of Electrical and Electronics Engineering, School of Engineering, AUT University, Auckland 1142, New Zealand. mirza.baig@aut.ac.nz
authors.forename: Mirza
authors.initials: M
authors.lastname: Mansoor Baig
authors.forename: Hamid
authors.initials: H
authors.lastname: Gholamhosseini
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Harrison
mesh_terms: D000465:Algorithms; D000758:Anesthesia; D000776:Anesthesiology / Q000295:instrumentation* / Q000379:methods*; D003658:Decision Making, Computer-Assisted; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D020896:Hypovolemia / Q000175:diagnosis / Q000503:physiopathology; D008297:Male; D016343:Monitoring, Intraoperative / Q000295:instrumentation / Q000379:methods; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*