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A Principal Component Regression Approach for Estimating Ventricular Repolarization Duration Variability

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Abstract

Ventricular repolarization duration (VRD) is affected by heart rate and autonomic control, and thus VRD varies in time in a similar way as heart rate. VRD variability is commonly assessed by determining the time differences between successive R- and T-waves, that is, RT intervals. Traditional methods for RT interval detection necessitate the detection of either T-wave apexes or offsets. In this paper, we propose a principal-component-regression- (PCR-) based method for estimating RT variability. The main benefit of the method is that it does not necessitate T-wave detection. The proposed method is compared with traditional RT interval measures, and as a result, it is observed to estimate RT variability accurately and to be less sensitive to noise than the traditional methods. As a specific application, the method is applied to exercise electrocardiogram (ECG) recordings.

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Correspondence to Mika P. Tarvainen.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Tarvainen, M.P., Laitinen, T., Lyyra-Laitinen, T. et al. A Principal Component Regression Approach for Estimating Ventricular Repolarization Duration Variability. EURASIP J. Adv. Signal Process. 2007, 058358 (2007) doi:10.1155/2007/58358

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Keywords

  • Heart Rate
  • Information Technology
  • Traditional Method
  • Time Difference
  • Quantum Information