Title :
The time-sequenced adaptive algorithm: application to morphological adaptation and arrhythmia onset detection
Author :
Finelli, C.J. ; Li, P.C. ; Jenkins, J.M. ; DiCarlo, L.A.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
An algorithm has been developed for morphologic adaptation and detection of arrhythmia onset. This is a computationally simple and patient-independent technique which adapts to subtle variations in electrogram morphology and promptly detects a change in morphology, as usually occurs at arrythmia onset. This technique also reduces the problem of costly detection time by quickly recognizing the onset of an arrhythmia within a few cardiac cycles. In a pilot study, the algorithm successfully adapted to electrogram morphology and identified the arrhythmia onset in a study of nine cases of onset of ventricular tachycardia during sinus rhythm
Keywords :
electrocardiography; waveform analysis; arrhythmia onset detection; cardiac cycles; morphological adaptation; patient-independent technique; sinus rhythm; time-sequenced adaptive algorithm; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Change detection algorithms; Face detection; Heart rate; Morphology; Rhythm; Robust stability; Strontium;
Conference_Titel :
Computers in Cardiology 1991, Proceedings.
Conference_Location :
Venice
Print_ISBN :
0-8186-2485-X
DOI :
10.1109/CIC.1991.169081