title: Robust adaptive parameter estimators in arrhythmia detection.
abstract: The authors consider the statistical analysis of threshold crossing intervals, as applied to estimation of tachycardia rates from intracavitary electrograms. The authors developed a class of robust algorithms designed to produce minimum variance estimates for tachycardia rates. The authors formulated the algorithms using order statistic filters, and obtained the minimum variance unbiased order statistic estimator. The potential gain in efficiency achieved by this approach is demonstrated via a representative example. The results indicated that the order statistics operator can produce dramatic reductions for typical errors in error variance as compared to linear estimators.
authors.affiliation: Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago 60616.
authors.forename: P M
authors.initials: PM
authors.lastname: Clarkson
authors.forename: Q
authors.initials: Q
authors.lastname: Fan
authors.forename: G A
authors.initials: GA
authors.lastname: Williamson
authors.forename: R
authors.initials: R
authors.lastname: Arzbaecher
mesh_terms: D000465:Algorithms; D017147:Defibrillators, Implantable; D006801:Humans; D008433:Mathematics; D013610:Tachycardia / Q000175:diagnosis*