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Methods Inf Med 2014; 53(04): 324-328
DOI: 10.3414/ME13-02-0040
Focus Theme – Original Articles
Schattauer GmbH

Modeling and Quantification of Repolarization Feature Dependency on Heart Rate

A. Minchole
1   Department of Computer Science, University of Oxford, Oxford, UK
2   Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
3   I3A, Universidad de Zaragoza, Zaragoza, Spain
,
E. Zacur
3   I3A, Universidad de Zaragoza, Zaragoza, Spain
,
E. Pueyo
2   Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
3   I3A, Universidad de Zaragoza, Zaragoza, Spain
,
P. Laguna
3   I3A, Universidad de Zaragoza, Zaragoza, Spain
2   Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
› Author Affiliations
Further Information

Publication History

received:14 October 2013

accepted:03 June 2014

Publication Date:
20 January 2018 (online)

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Summary

Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems”.

Objectives: This work aims at providing an efficient method to estimate the parameters of a non linear model including memory, previously proposed to characterize rate adaptation of repolarization indices.

Methods: The physiological restrictions on the model parameters have been included in the cost function in such a way that unconstrained optimization techniques such as descent optimization methods can be used for parameter estimation. The proposed method has been evaluated on electrocardiogram (ECG) recordings of healthy subjects performing a tilt test, where rate adaptation of QT and Tpeak-to-Tend (Tpe) intervals has been characterized.

Results: The proposed strategy results in an efficient methodology to characterize rate adaptation of repolarization features, improving the convergence time with respect to previous strategies. Moreover, Tpe interval adapts faster to changes in heart rate than the QT interval.

Conclusions: In this work an efficient estimation of the parameters of a model aimed at characterizing rate adaptation of repolarization features has been proposed. The Tpe interval has been shown to be rate related and with a shorter memory lag than the QT interval.

Keywords

Rate adaptation - T-peak to T-end - QT interval
 

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