title: Trend recognition in clinical signals using template-based methods.
abstract: The recognition of clinically significant trends in monitored signals plays an important role in many medical diagnostic applications. A template-based system technique to identify characteristic patterns in time-series data is described, based on fuzzy logic. Fuzzy set theory allows the creation of fuzzy templates from linguistic rules. The resulting fuzzy template system can accommodate multiple time signals, relative or absolute trends, and automatically generates a normalised "goodness of fit" score. The template approach was originally developed for monitoring during anaesthesia but has the potential to be useful in other domains that require temporal pattern recognition.
authors.affiliation: Department of Mechanical Engineering, University of Auckland, New Zealand.
authors.forename: R W
authors.initials: RW
authors.lastname: Jones
authors.forename: A
authors.initials: A
authors.lastname: Lowe
authors.forename: M J
authors.initials: MJ
authors.lastname: Harrison
mesh_terms: D001185:Artificial Intelligence; D004568:Electrodiagnosis; D005103:Expert Systems; D017143:Fuzzy Logic; D006801:Humans; D008432:Mathematical Computing; D016343:Monitoring, Intraoperative; D008991:Monitoring, Physiologic; D012815:Signal Processing, Computer-Assisted