000101193 001__ 101193 000101193 005__ 20230519145437.0 000101193 0247_ $$2doi$$a10.1109/JBHI.2020.2984647 000101193 0248_ $$2sideral$$a122314 000101193 037__ $$aART-2021-122314 000101193 041__ $$aeng 000101193 100__ $$0(orcid)0000-0002-1927-1762$$aSampedro-Puente, D.A. 000101193 245__ $$aCharacterization of Spatiooral Cardiac Action Potential Variability at Baseline and under ß-Adrenergic Stimulation by Combined Unscented Kalman Filter and Double Greedy Dimension Reduction 000101193 260__ $$c2021 000101193 5060_ $$aAccess copy available to the general public$$fUnrestricted 000101193 5203_ $$aObjective: Elevated spatiooral variability of human ventricular repolarization has been related to increased risk for ventricular arrhythmias and sudden cardiac death, particularly under ß-adrenergic stimulation (ß-AS). This work presents a methodology for theoretical characterization of temporal and spatial repolarization variability at baseline conditions and in response to ß-AS. For any measured voltage trace, the proposed methodology estimates the parameters and state variables of an underlying human ventricular action potential (AP) model by combining Double Greedy Dimension Reduction (DGDR) with automatic selection of biomarkers and the Unscented Kalman Filter (UKF). Such theoretical characterization can facilitate subsequent characterization of underlying variability mechanisms. Material and Methods: Given an AP trace, initial estimates for the ionic conductances in a stochastic version of the baseline human ventricular O'Hara et al. model were obtained by DGDR. Those estimates served to initialize and update model parameter estimates by the UKF method based on formulation of an associated nonlinear state-space representation and joint estimation of model parameters and state variables. Similarly, ß-AS-induced phosphorylation levels of cellular substrates were estimated by the DGDR-UKF methodology. Performance was tested by building an experimentally-calibrated population of virtual cells, from which synthetic AP traces were generated for baseline and ß-AS conditions. Results: The combined DGDR-UKF methodology led to 25% reduction in the error associated with estimation of ionic current conductances at baseline conditions and phosphorylation levels under ß-AS with respect to individual DGDR and UKF methods. This improvement was not at the expense of higher computational load, which was diminished by 90% with respect to the individual UKF method. Both temporal and spatial AP variability of repolarization were accurately characterized by the DGDR-UKF methodology. Conclusions: A combined DGDR-UKF methodology is proposed for parameter and state variable estimation of human ventricular cell models from available AP traces at baseline and under ß-AS. This methodology improves the estimation performance and reduces the convergence time with respect to individual DGDR and UKF methods and renders a suitable approach for computational characterization of spatiooral repolarization variability to be used for ascertainment of variability mechanisms and its relation to arrhythmogenesis. 000101193 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/DPI2016-75458-R$$9info:eu-repo/grantAgreement/EUR/ERC-2014-StG-638284$$9info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group$$9info:eu-repo/grantAgreement/ES/DGA-FSE/LMP124-18 000101193 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000101193 590__ $$a7.021$$b2021 000101193 592__ $$a1.799$$b2021 000101193 594__ $$a10.9$$b2021 000101193 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b4 / 57 = 0.07$$c2021$$dQ1$$eT1 000101193 593__ $$aBiotechnology$$c2021$$dQ1 000101193 591__ $$aMEDICAL INFORMATICS$$b7 / 31 = 0.226$$c2021$$dQ1$$eT1 000101193 593__ $$aHealth Information Management$$c2021$$dQ1 000101193 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b21 / 112 = 0.188$$c2021$$dQ1$$eT1 000101193 593__ $$aComputer Science Applications$$c2021$$dQ1 000101193 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b23 / 164 = 0.14$$c2021$$dQ1$$eT1 000101193 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000101193 700__ $$aRaphel, F. 000101193 700__ $$0(orcid)0000-0001-5175-3166$$aFernandez-Bes, J. 000101193 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, P.$$uUniversidad de Zaragoza 000101193 700__ $$aLombardi, D. 000101193 700__ $$0(orcid)0000-0002-1960-407X$$aPueyo, E.$$uUniversidad de Zaragoza 000101193 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac. 000101193 773__ $$g25, 1 (2021), 276-288$$pIEEE j. biomed. health inform.$$tIEEE journal of biomedical and health informatics$$x2168-2194 000101193 8564_ $$s780668$$uhttps://zaguan.unizar.es/record/101193/files/texto_completo.pdf$$yPostprint 000101193 8564_ $$s3568292$$uhttps://zaguan.unizar.es/record/101193/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000101193 909CO $$ooai:zaguan.unizar.es:101193$$particulos$$pdriver 000101193 951__ $$a2023-05-18-14:26:10 000101193 980__ $$aARTICLE