title: The graphical presentation of decision support information in an intelligent anaesthesia monitor.
abstract: This contribution examines the graphical presentation of decision support information generated by an intelligent monitor, named SENTINEL, developed for use during anaesthesia. Clinicians make diagnoses in real-time during operations by examining clinically significant trends in multiple signals. SENTINEL attempts to mimic this decision process by using a system of fuzzy trend templates. SENTINEL's implementation of fuzzy trend templates is capable of providing the dual fuzzy measures of belief and plausibility, which are derived from the theory of evidence. It is thus capable of generating fairly rich diagnostic decision support information. However, for SENTINEL to be effective, the visual presentation of this information must be intuitive to the anaesthetist, who may not be familiar with the theory of evidence. This paper discusses techniques that are being evaluated to meet the requirements of the SENTINEL anaesthesia monitor. Specifically, the paper presents methods for highlighting clinically significant trends in physiological (or derived) signals by superimposing a coloured band on the signal that reflects fuzzy output from the intelligent monitor. This paper also discusses the intuitive graphical presentation of binary diagnostic fuzzy measures, including their further interpretation and presentation as crisp "alarm" and "warning" conditions.
authors.affiliation: Department of Mechanical Engineering, University of Auckland, Private Bag 92019, Auckland, New Zealand.
authors.forename: A
authors.initials: A
authors.lastname: Lowe
authors.forename: R W
authors.initials: RW
authors.lastname: Jones
authors.forename: M J
authors.initials: MJ
authors.lastname: Harrison
mesh_terms: D000768:Anesthesia, General; D001185:Artificial Intelligence; D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D017143:Fuzzy Logic; D006801:Humans; D008991:Monitoring, Physiologic; D017603:Signal Detection, Psychological; D012984:Software