| Comparative analysis of methods for automatic detection and quantification of microvolt T-wave alternans. | |
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MedLine Citation:
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PMID: 19758833 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Microvolt T-wave alternans (TWA), consisting of every-other-beat changes in ECG T-wave morphology, is an index of susceptibility to malignant ventricular arrhythmias, requiring automatic techniques to be identified. Five of these, namely, 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 here to simulated and sample clinical data. The aim was to compare individual methods ability to properly identify stationary and time-varying TWA, avoiding false-positive detections. The MMAM provided false-positive TWA when applied to simulated ECGs affected by amplitude variability, but TWA. Stationary TWA was properly quantified by the MMAM and, occasionally, underestimated by all other methods. The AMFM properly identified time-varying TWA. By contrast, the FFTSM detected not-stationary TWA as stationary, the MMAM introduced a time-delay in the estimated TWA-amplitude signal, while the CDM and LLRM were reliable only in the presence of slow-varying TWA. Altogether, the AMFM accomplished the best compromise between the needs to avoid false-positive TWA and to detect and characterize true-positive TWA. Results of our simulation approach were useful to explain different TWA levels measured by each competing methods applied to sample Holter ECGs from healthy subjects and coronary artery disease patients. |
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Authors:
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Laura Burattini; Silvia Bini; Roberto Burattini |
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Publication Detail:
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Type: Comparative Study; Journal Article Date: 2009-09-15 |
Journal Detail:
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Title: Medical engineering & physics Volume: 31 ISSN: 1873-4030 ISO Abbreviation: Med Eng Phys Publication Date: 2009 Dec |
Date Detail:
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Created Date: 2009-11-25 Completed Date: 2010-02-18 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9422753 Medline TA: Med Eng Phys Country: England |
Other Details:
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Languages: eng Pagination: 1290-8 Citation Subset: IM |
Affiliation:
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Department of Biomedical, Electronics and Telecommunication Engineering, Polytechnic University of Marche, Ancona, Italy. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Arrhythmias, Cardiac / diagnosis, physiopathology Automation Case-Control Studies Computer Simulation Coronary Artery Disease / diagnosis, physiopathology* Electrocardiography / methods* False Positive Reactions Fourier Analysis Heart Rate Humans Likelihood Functions Signal Processing, Computer-Assisted* Time Factors |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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