000151355 001__ 151355
000151355 005__ 20251017144626.0
000151355 0247_ $$2doi$$a10.1109/TBME.2020.3028204
000151355 0248_ $$2sideral$$a126313
000151355 037__ $$aART-2021-126313
000151355 041__ $$aeng
000151355 100__ $$aMorales J.
000151355 245__ $$aModel-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation
000151355 260__ $$c2021
000151355 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151355 5203_ $$aObjective: 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.
000151355 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group$$9info:eu-repo/grantAgreement/EC/H2020/813120/EU/INtegrating Magnetic Resonance SPectroscopy and Multimodal Imaging for Research and Education in MEDicine/INSPiRE-MED$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 813120-INSPiRE-MED$$9info:eu-repo/grantAgreement/EC/H2020/813483/EU/INtegrating Functional Assessment measures for Neonatal Safeguard/INFANS$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 813483-INFANS
000151355 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000151355 590__ $$a4.756$$b2021
000151355 591__ $$aENGINEERING, BIOMEDICAL$$b37 / 98 = 0.378$$c2021$$dQ2$$eT2
000151355 592__ $$a1.298$$b2021
000151355 593__ $$aBiomedical Engineering$$c2021$$dQ1
000151355 594__ $$a9.4$$b2021
000151355 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000151355 700__ $$aMoeyersons J.
000151355 700__ $$0(orcid)0000-0001-5918-1043$$aArmanac P.$$uUniversidad de Zaragoza
000151355 700__ $$aOrini M.
000151355 700__ $$aFaes L.
000151355 700__ $$aOvereem S.
000151355 700__ $$aVan Gilst M.
000151355 700__ $$aVan Dijk J.
000151355 700__ $$aVan Huffel S.
000151355 700__ $$0(orcid)0000-0003-1272-0550$$aBailon R.$$uUniversidad de Zaragoza
000151355 700__ $$aVaron C.
000151355 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000151355 773__ $$g68, 6 (2021), 1882-1893$$pIEEE trans. biomed. eng.$$tIEEE Transactions on Biomedical Engineering$$x0018-9294
000151355 8564_ $$s3931016$$uhttps://zaguan.unizar.es/record/151355/files/texto_completo.pdf$$yVersión publicada
000151355 8564_ $$s3837422$$uhttps://zaguan.unizar.es/record/151355/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000151355 909CO $$ooai:zaguan.unizar.es:151355$$particulos$$pdriver
000151355 951__ $$a2025-10-17-14:24:18
000151355 980__ $$aARTICLE