000120070 001__ 120070
000120070 005__ 20240705134138.0
000120070 0247_ $$2doi$$a10.1109/RBME.2022.3220636
000120070 0248_ $$2sideral$$a130935
000120070 037__ $$aART-2022-130935
000120070 041__ $$aeng
000120070 100__ $$aSornmo, Leif
000120070 245__ $$aSpectral Analysis of Heart Rate Variability in Time-Varying Conditions and in the Presence of Confounding Factors
000120070 260__ $$c2022
000120070 5060_ $$aAccess copy available to the general public$$fUnrestricted
000120070 5203_ $$aThe tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerably, with emphasis on the handling of time-varying conditions and confounding factors. Time–frequency analysis holds since long an important position in HRV analysis, however, this technique cannot alone handle a mean heart rate or a respiratory frequency which vary over time. Overlapping frequency bands represents another critical condition which needs to be dealt with to produce accurate spectral measurements. The present survey offers a comprehensive account of techniques designed to handle such conditions and factors by providing a brief description of the main principles of the different methods. Several methods derive from a mathematical/statistical model, suggesting that the model can be used to simulate data used for performance evaluation. The inclusion of a respiratory signal, whether measured or derived, is another feature of many recent methods, e.g., used to guide the decomposition of the HRV signal so that signals related as well as unrelated to respiration can be analyzed. It is concluded that the development of new approaches to handling time-varying scenarios are warranted, as is benchmarking of performance evaluated in technical as well as in physiological/clinical terms.
000120070 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/T39-17R-BSICoS$$9info:eu-repo/grantAgreement/ES/DGA-FSE/Building Europe from Aragon$$9info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-104881RB-I00$$9info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-105674RB-I00
000120070 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000120070 590__ $$a17.6$$b2022
000120070 592__ $$a2.556$$b2022
000120070 591__ $$aENGINEERING, BIOMEDICAL$$b3 / 96 = 0.031$$c2022$$dQ1$$eT1
000120070 593__ $$aBiomedical Engineering$$c2022$$dQ1
000120070 594__ $$a27.8$$b2022
000120070 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000120070 700__ $$0(orcid)0000-0003-1272-0550$$aBailon, Raquel$$uUniversidad de Zaragoza
000120070 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, Pablo$$uUniversidad de Zaragoza
000120070 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000120070 773__ $$g17 (2022), 322-341$$pIEEE rev. biomed. eng.$$tIEEE reviews in biomedical engineering$$x1937-3333
000120070 8564_ $$s4261554$$uhttps://zaguan.unizar.es/record/120070/files/texto_completo.pdf$$yPostprint
000120070 8564_ $$s3766943$$uhttps://zaguan.unizar.es/record/120070/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000120070 909CO $$ooai:zaguan.unizar.es:120070$$particulos$$pdriver
000120070 951__ $$a2024-07-05-12:46:01
000120070 980__ $$aARTICLE