Title
Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation
Author
Morales, John (Katholieke Universiteit Leuven; ESAT - STADIUS)
Moeyersons, Jonathan (Katholieke Universiteit Leuven; ESAT - STADIUS)
Armanac, Pablo (Biomaterials and Nanomedicine (CIBER-BBN); University of Zaragoza)
Orini, Michele (University College London)
Faes, Luca (Università degli Studi di Palermo)
Overeem, Sebastiaan (Eindhoven University of Technology; The Sleep Medicine Center Kempenhaeghe)
Van Gilst, Merel (Eindhoven University of Technology; The Sleep Medicine Center Kempenhaeghe)
Van Dijk, Johannes (Eindhoven University of Technology; The Sleep Medicine Center Kempenhaeghe)
Van Huffel, Sabine (Katholieke Universiteit Leuven; ESAT - STADIUS)
Bailon, Raquel (University of Zaragoza)
Varon, Carolina (TU Delft Signal Processing Systems; ESAT - STADIUS; Katholieke Universiteit Leuven)
Date
2021
Abstract
Objective: Respiratory sinus arrhythmia (RSA) refers to heart rate oscillations synchronous with respiration, and it is one of the major representations of cardiorespiratory coupling. Its strength has been suggested as a biomarker to monitor different conditions, and diseases. Some approaches have been proposed to quantify the RSA, but it is unclear which one performs best in specific scenarios. The main objective of this study is to compare seven state-of-the-art methods for RSA quantification using data generated with a model proposed to simulate, and control the RSA. These methods are also compared, and evaluated on a real-life application, for their ability to capture changes in cardiorespiratory coupling during sleep. Methods: A simulation model is used to create a dataset of heart rate variability, and respiratory signals with controlled RSA, which is used to compare the RSA estimation approaches. To compare the methods objectively in real-life applications, regression models trained on the simulated data are used to map the estimates to the same measurement scale. Results, and conclusion: RSA estimates based on cross entropy, time-frequency coherence, and subspace projections showed the best performance on simulated data. In addition, these estimates captured the expected trends in the changes in cardiorespiratory coupling during sleep similarly. Significance: An objective comparison of methods for RSA quantification is presented to guide future analyses. Also, the proposed simulation model can be used to compare existing, and newly proposed RSA estimates. It is freely accessible online.
Subject
Cardiorespiratory coupling
heart rate variability
respiratory sinus arrhythmia
To reference this document use:
http://resolver.tudelft.nl/uuid:cd5dd598-1708-4cb8-81a4-e5f5014b2994
DOI
https://doi.org/10.1109/TBME.2020.3028204
ISSN
0018-9294
Source
IEEE Transactions on Biomedical Engineering, 68 (6), 1882-1893
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2021 John Morales, Jonathan Moeyersons, Pablo Armanac, Michele Orini, Luca Faes, Sebastiaan Overeem, Merel Van Gilst, Johannes Van Dijk, Sabine Van Huffel, Raquel Bailon, Carolina Varon