DocumentCode :
3036423
Title :
A robust sequential detection algorithm for cardiac arrhythmia classification
Author :
Clarkson, Peter M. ; Chen, Szi Wen ; Fan, QZ
Author_Institution :
Biomed. Eng. Center, Ohio State Univ., Columbus, OH, USA
Volume :
2
fYear :
1995
fDate :
9-12 May 1995
Firstpage :
1181
Abstract :
We describe a modified sequential probability ratio test (SPRT) for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT) in measured surface electrocardiograms. The algorithm uses a novel regularity measure dubbed blanking variability (BV) applied to threshold crossings from the measured ECG. Blanking variability corresponds to the normalized rate of change of cardiac rate as the blanking interval is varied. The algorithm has been trained and tested using separate subsets drawn from the MIT-BIH malignant arrhythmia database. BV values are modeled using a truncated Gaussian distribution, and parameter values are derived by averaging over the training component of the database. In testing, the algorithm achieved an overall classification accuracy of 95%
Keywords :
Gaussian distribution; electrocardiography; medical signal processing; signal detection; ECG; MIT-BIH malignant arrhythmia database; algorithm; blanking variability; cardiac arrhythmia classification; cardiac rate; classification accuracy; robust sequential detection algorithm; sequential probability ratio test; surface electrocardiograms; testing; threshold crossings; training component; truncated Gaussian distribution; ventricular fibrillation; ventricular tachycardia; Blanking; Cancer; Change detection algorithms; Databases; Detection algorithms; Electrocardiography; Fibrillation; Robustness; Sequential analysis; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
ISSN :
1520-6149
Print_ISBN :
0-7803-2431-5
Type :
conf
DOI :
10.1109/ICASSP.1995.480448
Filename :
480448
Link To Document :
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