DocumentCode :
1141208
Title :
Adaptive classification of myocardial electrogram waveforms
Author :
Gibb, William J. ; Auslander, David M. ; Griffin, Jerry C.
Author_Institution :
Cardiovasular Res. Inst., California Univ., San Francisco, CA, USA
Volume :
41
Issue :
8
fYear :
1994
Firstpage :
804
Lastpage :
808
Abstract :
The shape of myocardial electrogram complexes can change gradually in response to electrical and physiological transients. These changes could affect the reliability of morphologic-based electrogram classifiers proposed for use in implantable cardioverters. Here the authors present a method of detecting gradual changes in the shape of electrogram complexes and evaluate the method by incorporating it into a simple adaptive classification scheme. Of the six subjects recruited to take part in a previous comparative study of myocardial electrogram features, the authors observed extensive morphologic drift of normal sinus beats in two subjects. The results indicate that the adaptive classification scheme proposed here can reduce observed classification error rates compared to rates obtained without adaptation.
Keywords :
bioelectric potentials; electrocardiography; medical signal processing; muscle; adaptive classification; classification error rates reduction; electrical transients; gradual shape changes detection; implantable cardioverters; morphologic-based electrogram classifiers reliability; myocardial electrogram features; myocardial electrogram waveforms; normal sinus beats; physiological transients; Cardiology; Electrocardiography; Error analysis; Heart rate; Humans; Myocardium; Recruitment; Rhythm; Shape; Surface morphology; Algorithms; Defibrillators, Implantable; Electrocardiography; Electrodes; Humans; Reference Values; Tachycardia;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.310096
Filename :
310096
Link To Document :
بازگشت