Literature DB >> 20920875

Automatic microvolt T-wave alternans identification in relation to ECG interferences surviving preprocessing.

Laura Burattini1, Silvia Bini, Roberto Burattini.   

Abstract

The aim was to investigate the effect of interferences surviving preprocessing (residual noise, baseline wanderings, respiration modulation, replaced beats, missed beats and T-waves misalignment) on automatic identification of T-wave alternans (TWA), an ECG index of risk for sudden cardiac death. The procedures denominated fast-Fourier-transform spectral method (FFTSM), complex-demodulation method (CDM), modified-moving-average method (MMAM), Laplacian-likelihood-ratio method (LLRM), and adaptive-match-filter method (AMFM) were applied to interferences-corrupted synthetic ECG tracings and Holter ECG recordings from control-healthy subjects (CH-group; n=25) and acute-myocardial-infarction patients (AMI group; n=25). The presence of interferences in simulated data caused detection of false-positive TWA by all techniques but the FFTSM and AMFM. Clinical applications evidenced a discrepancy in that the FFTSM and LLRM detected no more than one TWA case in each population, whereas the CDM, MMAM, and AMFM detected TWA in all CH-subjects and AMI-patients, with significantly lower TWA amplitude in the former group. Because the AMFM is not prone to false-positive TWA detections, the latter finding suggests TWA as a phenomenon having continuously changing amplitude from physiological to pathological conditions. Only occasional detection of TWA by the FFTSM and LLRM in clinics can be ascribed to their limited ability in identifying TWA in the presence of interferences surviving preprocessing.
Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 20920875     DOI: 10.1016/j.medengphy.2010.08.014

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  6 in total

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Authors:  Laura Burattini; Sumche Man; Roberto Burattini; Cees A Swenne
Journal:  Ann Noninvasive Electrocardiol       Date:  2012-04       Impact factor: 1.468

2.  A unified procedure for detecting, quantifying, and validating electrocardiogram T-wave alternans.

Authors:  H Naseri; H Pourkhajeh; M R Homaeinezhad
Journal:  Med Biol Eng Comput       Date:  2013-05-22       Impact factor: 2.602

3.  Dependency of exercise-induced T-wave alternans predictive power for the occurrence of ventricular arrhythmias from heart rate.

Authors:  Laura Burattini; Sumche Man; Sandro Fioretti; Francesco Di Nardo; Cees A Swenne
Journal:  Ann Noninvasive Electrocardiol       Date:  2014-11-04       Impact factor: 1.468

4.  Heart Rate-Dependent Hysteresis of T-Wave Alternans in Primary Prevention ICD Patients.

Authors:  Laura Burattini; Sumche Man; Sandro Fioretti; Francesco Di Nardo; Cees A Swenne
Journal:  Ann Noninvasive Electrocardiol       Date:  2015-12-16       Impact factor: 1.468

5.  T-Wave Alternans in Nonpathological Preterm Infants.

Authors:  Ilaria Marcantoni; Agnese Sbrollini; Gloria Agostinelli; Francesca Chiara Surace; Massimo Colaneri; Micaela Morettini; Marco Pozzi; Laura Burattini
Journal:  Ann Noninvasive Electrocardiol       Date:  2020-01-27       Impact factor: 1.468

6.  A time-domain hybrid analysis method for detecting and quantifying T-wave alternans.

Authors:  Xiangkui Wan; Kanghui Yan; Linlin Zhang; Yanjun Zeng
Journal:  Comput Math Methods Med       Date:  2014-04-03       Impact factor: 2.238

  6 in total

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