Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/73856
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Type: Conference paper
Title: Beat-to-beat spatial and temporal analysis for QRS-T morphology
Author: Hasan, M.
Abbott, D.
Baumert, M.
Citation: Engineering Innovation in Global Health: Proceedings of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, held in San Diego, August 28-September 1, 2012: pp. 4193-4195
Publisher: IEEE
Publisher Place: CD
Issue Date: 2012
Series/Report no.: IEEE Engineering in Medicine and Biology Society Conference Proceedings
ISBN: 1457717875
9781424441198
ISSN: 1557-170X
Conference Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (34th : 2012 : San Diego)
Statement of
Responsibility: 
Muhammad Asraful Hasan, Derek Abbott and Mathias Baumert
Abstract: The aim of this study was to investigate beat-to-beat variations of spatial and temporal QRS and T loop morphology for identifying myocardial infarction (MI) patients. We investigated short-term 12-lead ECG recordings of 84 MI patients (22 female, mean age 63 ± 12 years and 62 male, mean age 56 ± 10 years) and 69 healthy control subjects (17 female, mean age 42 ± 18 years and 52 male, mean age 40 ± 13 years). To quantify spatial and temporal variations in QRS complex and T-wave morphology, we defined two descriptor parameters: point-to-point distance variability (DV) and mean loop length (MLL). These parameters were extracted from the reconstructed vector ECG, using singular value decomposition. The results showed that the beat-to-beat spatiotemporal point-to-point distance variability for QRS and T loops (DVQRS; 0.13±0.04 vs. 0.10±0.04, p < 0.0001 and DVT; 0.16±0.07 vs. 0.13±0.06, p < 0.05), were significantly higher in MI subjects compared to control subjects. In addition, the mean loop length of QRS and T loops were significantly higher in control subjects than MI (p < 0.001), respectively. In conclusion, the beat-to-beat spatiotemporal DV and MLL may be useful for characterizing conduction and repolarization characteristics in patients with MI.
Keywords: Nonlinear dynamics in biomedical signals; biomedical simulation involving signal processing
Rights: Copyright © 2012 IEEE Engineering in Medicine and Biology Society. All rights reserved.
RMID: 0020122324
DOI: 10.1109/EMBC.2012.6346891
Description (link): http://embs.papercept.net/conferences/conferences/EMBC12/program/EMBC12_ContentListWeb_3.html
Appears in Collections:Electrical and Electronic Engineering publications

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