000086294 001__ 86294
000086294 005__ 20200716101452.0
000086294 0247_ $$2doi$$a10.1109/JBHI.2018.2884644
000086294 0248_ $$2sideral$$a108932
000086294 037__ $$aART-2019-108932
000086294 041__ $$aeng
000086294 100__ $$aVaron, Carolina
000086294 245__ $$aUnconstrained estimation of HRV indices after removing respiratory influences from heart rate
000086294 260__ $$c2019
000086294 5060_ $$aAccess copy available to the general public$$fUnrestricted
000086294 5203_ $$aObjective: This paper proposes an approach to better estimate the sympathovagal balance (SB) and the respiratory sinus arrhythmia (RSA) after separating respiratory influences from the heart rate (HR).
Methods: The separation is performed using orthogonal subspace projections and the approach is first tested using simulated HR and respiratory signals with different spectral properties. Then, RSA and SB are estimated during autonomic blockade and stress using the proposed approach and the classical heart rate variability (HRV) analysis. Both real and ECG-derived respiration (EDR) are used and the reliability of the EDR is evaluated.
Results: Mean absolute percentage errors lower than 1% were obtained after removing previously known respiratory signals from simulated HR. The proposed indices were able to improve the quantification of SB during autonomic withdrawal. In the stress data, differences ( $p < 0.003 ) among relaxed and stressful phases were found with the proposed approach, using both the real respiration and the EDR, but they disappeared when using the classical HRV.
Conclusion: A better assessment of the autonomic nervous system' response to pharmacological blockade and stress can be achieved after removing respiratory influences from HR, and this can be done using either the real respiration or the EDR. Significance: This work can be used to better identify vagal withdrawal and increased sympathetic activation when the classical HRV analysis fails due to the respiratory influences on HR. Furthermore, it can be computed using only the ECG, which is an advantage when developing wearable systems with limited number of sensors.
000086294 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T96$$9info:eu-repo/grantAgreement/EC/FP7/339804/EU/Biomedical Data Fusion using Tensor based Blind Source Separation/BIOTENSORS$$9info:eu-repo/grantAgreement/EC/H2020/745755/EU/Wearable Cardiorespiratory Monitor/WECARMON$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 745755-WECARMON$$9info:eu-repo/grantAgreement/ES/ISCIII/CIBER-BBN$$9info:eu-repo/grantAgreement/ES/UZ/UZ2018-TEC-05
000086294 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000086294 590__ $$a5.223$$b2019
000086294 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b15 / 156 = 0.096$$c2019$$dQ1$$eT1
000086294 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b5 / 59 = 0.085$$c2019$$dQ1$$eT1
000086294 591__ $$aMEDICAL INFORMATICS$$b1 / 27 = 0.037$$c2019$$dQ1$$eT1
000086294 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b12 / 109 = 0.11$$c2019$$dQ1$$eT1
000086294 592__ $$a1.306$$b2019
000086294 593__ $$aBiotechnology$$c2019$$dQ1
000086294 593__ $$aHealth Information Management$$c2019$$dQ1
000086294 593__ $$aElectrical and Electronic Engineering$$c2019$$dQ1
000086294 593__ $$aComputer Science Applications$$c2019$$dQ1
000086294 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000086294 700__ $$0(orcid)0000-0001-8742-0072$$aLázaro Plaza, Jesús$$uUniversidad de Zaragoza
000086294 700__ $$0(orcid)0000-0003-4068-127X$$aBolea, Juan
000086294 700__ $$0(orcid)0000-0003-2596-7237$$aHernando, Alberto
000086294 700__ $$aAguiló, Jordi
000086294 700__ $$0(orcid)0000-0001-7285-0715$$aGil, Eduardo$$uUniversidad de Zaragoza
000086294 700__ $$aVan Huffel, Sabine
000086294 700__ $$0(orcid)0000-0003-1272-0550$$aBailón, Raquel$$uUniversidad de Zaragoza
000086294 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000086294 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000086294 773__ $$g23, 6 (2019), 2386-2397$$pIEEE j. biomed. health inform.$$tIEEE journal of biomedical and health informatics$$x2168-2194
000086294 8564_ $$s257698$$uhttps://zaguan.unizar.es/record/86294/files/texto_completo.pdf$$yPostprint
000086294 8564_ $$s152690$$uhttps://zaguan.unizar.es/record/86294/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000086294 909CO $$ooai:zaguan.unizar.es:86294$$particulos$$pdriver
000086294 951__ $$a2020-07-16-09:07:05
000086294 980__ $$aARTICLE