On the robustness of multiscale indices for long-term monitoring in cardiac signals

El-Yaagoubi, Mohammed and Goya Esteban, Rebeca and Jabrane, Younes and Muñoz Romero, Sergio and García Alberola, Arcadi and Rojo Álvarez, José (2019). On the robustness of multiscale indices for long-term monitoring in cardiac signals. "Entropy", v. 21 (n. 6); pp. 594-616. ISSN 1099-4300. https://doi.org/10.3390/e21060594.


Title: On the robustness of multiscale indices for long-term monitoring in cardiac signals
  • El-Yaagoubi, Mohammed
  • Goya Esteban, Rebeca
  • Jabrane, Younes
  • Muñoz Romero, Sergio
  • García Alberola, Arcadi
  • Rojo Álvarez, José
Item Type: Article
Título de Revista/Publicación: Entropy
Date: 2019
ISSN: 1099-4300
Volume: 21
Freetext Keywords: Nonlinear dynamics, Multiscale indices, Cardiac risk stratification, Holter, Long term monitoring, Multiscale entropy, Multifractal spectrum, Multiscale time irreversibility
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (3MB) | Preview


The identification of patients with increased risk of Sudden Cardiac Death (SCD) has been widely studied during recent decades, and several quantitative measurements have been proposed from the analysis of the electrocardiogram (ECG) stored in 1-day Holter recordings. Indices based on nonlinear dynamics of Heart Rate Variability (HRV) have shown to convey predictive information in terms of factors related with the cardiac regulation by the autonomous nervous system, and among them, multiscale methods aim to provide more complete descriptions than single-scale based measures. However, there is limited knowledge on the suitability of nonlinear measurements to characterize the cardiac dynamics in current long-term monitoring scenarios of several days. Here, we scrutinized the long-term robustness properties of three nonlinear methods for HRV characterization, namely, the Multiscale Entropy (MSE), the Multiscale Time Irreversibility (MTI), and the Multifractal Spectrum (MFS). These indices were selected because all of them have been theoretically designed to take into account the multiple time scales inherent in healthy and pathological cardiac dynamics, and they have been analyzed so far when monitoring up to 24 h of ECG signals, corresponding to about 20 time scales. We analyzed them in 7-day Holter recordings from two data sets, namely, patients with Atrial Fibrillation and with Congestive Heart Failure, by reaching up to 100 time scales. In addition, a new comparison procedure is proposed to statistically compare the poblational multiscale representations in different patient or processing conditions, in terms of the non-parametric estimation of confidence intervals for the averaged median differences. Our results show that variance reduction is actually obtained in the multiscale estimators. The MSE (MTI) exhibited the lowest (largest) bias and variance at large scales, whereas all the methods exhibited a consistent description of the large-scale processes in terms of multiscale index robustness. In all the methods, the used algorithms could turn to give some inconsistency in the multiscale profile, which was checked not to be due to the presence of artifacts, but rather with unclear origin. The reduction in standard error for several-day recordings compared to one-day recordings was more evident in MSE, whereas bias was more patently present in MFS. Our results pave the way of these techniques towards their use, with improved algorithmic implementations and nonparametric statistical tests, in long-term cardiac Holter monitoring scenarios.

Funding Projects

Government of SpainTEC2016-75161-C2-1-RFINALEUniversidad Rey Juan CarlosInvestigación traslacional y transferencia de un nuevo sistema de electrofisiología cardiaca no inavasiva de alta resolución
Government of SpainTEC2016-81900-REDTKERMESUniversidad de ValenciaAvances en métodos núcleo para datos estructurados

More information

Item ID: 67119
DC Identifier: https://oa.upm.es/67119/
OAI Identifier: oai:oa.upm.es:67119
DOI: 10.3390/e21060594
Official URL: https://www.mdpi.com/1099-4300/21/6/594
Deposited by: Memoria Investigacion
Deposited on: 18 May 2021 06:40
Last Modified: 18 May 2021 06:40
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM