Literature DB >> 9214830

A robust sequential detection algorithm for cardiac arrhythmia classification.

S W Chen1, P M Clarkson, Q Fan.   

Abstract

In [1] qnd [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%.

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Year:  1996        PMID: 9214830     DOI: 10.1109/10.541254

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  4 in total

1.  Combined wavelet transformation and radial basis neural networks for classifying life-threatening cardiac arrhythmias.

Authors:  A S al-Fahoum; I Howitt
Journal:  Med Biol Eng Comput       Date:  1999-09       Impact factor: 2.602

2.  Sequential algorithm for life threatening cardiac pathologies detection based on mean signal strength and EMD functions.

Authors:  Emran M Abu Anas; Soo Y Lee; Md K Hasan
Journal:  Biomed Eng Online       Date:  2010-09-04       Impact factor: 2.819

3.  Cardiac arrhythmia classification using autoregressive modeling.

Authors:  Dingfei Ge; Narayanan Srinivasan; Shankar M Krishnan
Journal:  Biomed Eng Online       Date:  2002-11-13       Impact factor: 2.819

4.  Life-threatening ventricular arrhythmia recognition by nonlinear descriptor.

Authors:  Yan Sun; Kap Luk Chan; Shankar Muthu Krishnan
Journal:  Biomed Eng Online       Date:  2005-01-24       Impact factor: 2.819

  4 in total

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