Literature DB >> 8070808

Multiway sequential hypothesis testing for tachyarrhythmia discrimination.

N V Thakor1, A Natarajan, G F Tomaselli.   

Abstract

A multiway sequential hypothesis testing (M-SHT) algorithm is proposed for simultaneous discrimination of cardiac tachyarrhythmias--supraventricular tachycardia (SVT) and ventricular tachycardia (VT)--from normal sinus rhythm (NSR). The M-SHT algorithm calculates a likelihood function from atrio-ventricular delay measurements, and compares this function with thresholds derived from specified error probabilities for the arrhythmias to be discriminated. Performance of this algorithm was evaluated on dual channel endocardial electrograms recorded in the cardiac electrophysiology laboratory. Two databases were developed, one for development of the algorithm and another for evaluation. The M-SHT algorithm accurately classified 26 out of 28 NSR (2 misclassified as SVT), 31 out of 31 cases of SVT, and 41 out of 43 VT (2 misclassified as NSR). The average length of time taken for classification of the three rhythms was: 3.6 s for NSR, 5.0 s for SVT, and 1.6 s for VT. Unique features of this algorithm are that acceptable error rates for each arrhythmia are independently specified and accuracy can be traded off for a faster detection time, and vice versa.

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Year:  1994        PMID: 8070808     DOI: 10.1109/10.293223

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


  5 in total

1.  Fuzzy clustered probabilistic and multi layered feed forward neural networks for electrocardiogram arrhythmia classification.

Authors:  Hassan Hamsa Haseena; Abraham T Mathew; Joseph K Paul
Journal:  J Med Syst       Date:  2009-08-11       Impact factor: 4.460

2.  Classification of arrhythmia using hybrid networks.

Authors:  Hassan H Haseena; Paul K Joseph; Abraham T Mathew
Journal:  J Med Syst       Date:  2010-03-10       Impact factor: 4.460

3.  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

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

5.  Wavelet Based Method for Congestive Heart Failure Recognition by Three Confirmation Functions.

Authors:  K Daqrouq; A Dobaie
Journal:  Comput Math Methods Med       Date:  2016-02-02       Impact factor: 2.238

  5 in total

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