A robust sequential detection algorithm for cardiac arrhythmia classification

Szi Wen Chen*, Peter M. Clarkson, Qi Fan

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

57 Scopus citations

Abstract

In [1] and [2] Thakor et al. describe a sequential probability ratio test (SPRT) based on threshold crossing intervals (TCI) for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT). However, in applying their algorithm to data from the MIT-BIH malignant arrhythmia database, we observed some overlap in the distributions of TCI for VF and VT resulting in 16% overall error rate for the discrimination. In this communication, we describe a modified SPRT algorithm, using a new feature dubbed blanking variability (BV) as the basis for discrimination. Using the MIT-BIH database, the preliminary results showed that the proposed method decreases the overall error rate to 5%.

Original languageEnglish
Pages (from-to)1120-1125
Number of pages6
JournalIEEE Transactions on Biomedical Engineering
Volume43
Issue number11
DOIs
StatePublished - 1996
Externally publishedYes

Fingerprint

Dive into the research topics of 'A robust sequential detection algorithm for cardiac arrhythmia classification'. Together they form a unique fingerprint.

Cite this