151355 20251017144626.0 doi 10.1109/TBME.2020.3028204 sideral 126313 ART-2021-126313 eng Morales J. Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation 2021 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group info:eu-repo/grantAgreement/EC/H2020/813120/EU/INtegrating Magnetic Resonance SPectroscopy and Multimodal Imaging for Research and Education in MEDicine/INSPiRE-MED This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 813120-INSPiRE-MED info:eu-repo/grantAgreement/EC/H2020/813483/EU/INtegrating Functional Assessment measures for Neonatal Safeguard/INFANS This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 813483-INFANS info:eu-repo/semantics/openAccess by-nc-nd https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es 4.756 2021 ENGINEERING, BIOMEDICAL 37 / 98 = 0.378 2021 Q2 T2 1.298 2021 Biomedical Engineering 2021 Q1 9.4 2021 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Moeyersons J. Armanac P. Universidad de Zaragoza (orcid)0000-0001-5918-1043 Orini M. Faes L. Overeem S. Van Gilst M. Van Dijk J. Van Huffel S. Bailon R. Universidad de Zaragoza (orcid)0000-0003-1272-0550 Varon C. 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 68, 6 (2021), 1882-1893 IEEE trans. biomed. eng. IEEE Transactions on Biomedical Engineering 0018-9294 3931016 http://zaguan.unizar.es/record/151355/files/texto_completo.pdf Versión publicada 3837422 http://zaguan.unizar.es/record/151355/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:151355 articulos driver 2025-10-17-14:24:18 ARTICLE