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Ventricular fibrillation detection by a regression test on the autocorrelation function.
- Source :
- Medical & Biological Engineering & Computing; 1987, Vol. 25 Issue 3, p241-249, 9p
- Publication Year :
- 1987
-
Abstract
- The paper investigates quantitative differences in the signal characteristics of ventricular fibrillation (VF) and other cardiac arrhythmias. The analysis procedure comprises two steps: calculation of a short-term autocorrelation function (ACF) followed by a regression test on a plot of peak magnitudes of the ACF against lag values (the ACF/lag plot). We detect VF by testing the hypothesis that the ACF/lag plot of VF does not pass a linear regression test. Analysis of 31 separate episodes (of VF and other ventricular arrhythmias), each comprising three successive segments of 1·5s each produced the following results: (1) 100 per cent sensitivity (Se), 62 per cent specificity (Sp) and 74 per cent test efficiency (TE) after analysis of the first segment; (2) 100 per cent Se, 86 per cent Sp and 90 per cent TE after the second segment; and (3) 100 per cent Se, 100 per cent Sp and 100 per cent TE after the third segment. This method quantifies the notion that VF signals are nonperiodic with a random amplitude distribution, whereas ventricular tachycardia (VT) signals are usually periodic with more uniform amplitude distributions. Accurate discrimination and identification of VF can be very important in intensive-care settings, as well as in the design of automatic cardioverters and defibrillators. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01400118
- Volume :
- 25
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Medical & Biological Engineering & Computing
- Publication Type :
- Academic Journal
- Accession number :
- 73023074
- Full Text :
- https://doi.org/10.1007/BF02447420