000098284 001__ 98284
000098284 005__ 20230914083306.0
000098284 0247_ $$2doi$$a10.23919/CinC49843.2019.9005628
000098284 0248_ $$2sideral$$a122002
000098284 037__ $$aART-2019-122002
000098284 041__ $$aeng
000098284 100__ $$aVaron, C.
000098284 245__ $$aQuantification of Linear and Nonlinear Cardiorespiratory Interactions under Autonomic Nervous System Blockade
000098284 260__ $$c2019
000098284 5060_ $$aAccess copy available to the general public$$fUnrestricted
000098284 5203_ $$aThis paper proposes a methodology to extract both linear and nonlinear respiratory influences from the heart rate variability (HRV), by decomposing the HRV into a respiratory and a residual component. This methodology is based on least-squares support vector machines (LS-SVM) formulated for nonlinear function estimation. From this decomposition, a better estimation of the respiratory sinus arrhythmia (RSA) and the sympathovagal balance (SB) can be achieved. These estimates are first analyzed during autonomic blockade and an orthostatic maneuver, and then compared against the classical HRV and a model that considers only linear interactions. Results are evaluated using surrogate data analysis and they indicate that the classical HRV and the linear model underestimate the cardiorespiratory interactions. Moreover, the linear and nonlinear interactions appear to be mediated by different control mechanisms. These findings will allow to better assess the ANS and to improve the understanding of the interactions within the cardiorespiratory system.
000098284 536__ $$9info:eu-repo/grantAgreement/EC/FP7/339804/EU/Biomedical Data Fusion using Tensor based Blind Source Separation/BIOTENSORS$$9info:eu-repo/grantAgreement/ES/MINECO-FEDER/RTI2018-097723-B-I00
000098284 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000098284 592__ $$a0.296$$b2019
000098284 593__ $$aComputer Science (miscellaneous)$$c2019
000098284 593__ $$aCardiology and Cardiovascular Medicine$$c2019
000098284 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000098284 700__ $$aHendrikx, D.
000098284 700__ $$aBolea, J.
000098284 700__ $$aLaguna, P.
000098284 700__ $$0(orcid)0000-0003-1272-0550$$aBailón, R.$$uUniversidad de Zaragoza
000098284 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000098284 773__ $$g46 (2019), [4 pp]$$pComput. cardiol.$$tComputing in Cardiology$$x2325-8861
000098284 8564_ $$s103149$$uhttps://zaguan.unizar.es/record/98284/files/texto_completo.pdf$$yVersión publicada
000098284 8564_ $$s2924045$$uhttps://zaguan.unizar.es/record/98284/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000098284 909CO $$ooai:zaguan.unizar.es:98284$$particulos$$pdriver
000098284 951__ $$a2023-09-13-10:56:10
000098284 980__ $$aARTICLE