A T-wave alternans assessment method based on least squares curve fitting technique

Wan, Xiangkui and Li, Yan ORCID: https://orcid.org/0000-0002-4694-4926 and Xia, Chong and Wu, Minghu and Liang, Jin and Wang, Na (2016) A T-wave alternans assessment method based on least squares curve fitting technique. Measurement, 86. pp. 93-100. ISSN 0263-2241


Abstract

T-wave alternans (TWA) is hypothesized to be related with patients at an increased risk for ventricular arrhythmias. A novel TWA assessment method based on least squares curve fitting techniques (LSCF) is presented in this paper. Real clinical ECG recordings and simulated ECG signals containing additive TWAs and noise are used to test the efficiency of the LSCF. The results are also compared with those by the Modified Moving Average(MMA) algorithm. The experimental results demonstrate that the LSCF is efficiency and promising in detecting and measuring TWAs.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Date Deposited: 02 Mar 2017 05:50
Last Modified: 02 Mar 2017 23:44
Uncontrolled Keywords: electrocardiograph (ECG), T-wave alternans, curve fitting
Fields of Research (2008): 09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
Fields of Research (2020): 40 ENGINEERING > 4006 Communications engineering > 400607 Signal processing
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: https://doi.org/10.1016/j.measurement.2016.01.046
URI: http://eprints.usq.edu.au/id/eprint/30563

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