000153003 001__ 153003
000153003 005__ 20250404131341.0
000153003 0247_ $$2doi$$a10.22489/Cinc.2020.094
000153003 0248_ $$2sideral$$a143489
000153003 037__ $$aART-2020-143489
000153003 041__ $$aeng
000153003 100__ $$0(orcid)0000-0003-4273-5403$$aSánchez, Carlos
000153003 245__ $$aSafety Ranges for Heart Rate Variability Parameters in Hyperbaric Environments
000153003 260__ $$c2020
000153003 5060_ $$aAccess copy available to the general public$$fUnrestricted
000153003 5203_ $$aThe Autonomic Nervous System (ANS) tries to maintain homeostasis in hyperbaric environments, but its activity may present large variability between subjects. The aim of this study is to establish safety ranges for ANS-related indices derived from the electrocardiographic signal (ECG) during diving and use them to identify subjects with abnormal ANS response and avoid potential diving accidents.
A database with ECG recordings from 28 subjects introduced into a hyperbaric chamber was used. During immersion, five stages were studied at 1, 3 and 5 atm during descent and ascent. Indices of heart rate variability, extracted from ECG, reflecting the sympathetic and parasympathetic ANS response, were calculated and regularised with respect to their values at the initial stage at 1 atm.
In particular, four time-related parameters extracted from the RR series and four frequency parameters based on the powers of the low and high frequency bands were used. High inter-subject variability in the ANS response was observed in all stages. The eight parameters were analysed for each stage and, as a result, some subjects presented highly uncommon responses with higher chances
of suffering a diving accident, reflected in many parameters out of the interquartile range. This allows establishing safety ranges for ANS-related parameters that can help in the identification of subjects with potential health risk.
000153003 536__ $$9info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-095936-B-I00$$9info:eu-repo/grantAgreement/ES/UZ/CUD2019-10$$9info:eu-repo/grantAgreement/ES/UZ/UZCUD2019-TEC-01
000153003 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000153003 592__ $$a0.257$$b2020
000153003 593__ $$aComputer Science (miscellaneous)$$c2020
000153003 593__ $$aCardiology and Cardiovascular Medicine$$c2020
000153003 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000153003 700__ $$0(orcid)0000-0003-2596-7237$$aHernando, Alberto
000153003 700__ $$0(orcid)0000-0003-4068-127X$$aBolea, Juan
000153003 700__ $$0(orcid)0000-0002-4746-3139$$aIzquierdo, David
000153003 700__ $$0(orcid)0000-0003-0630-4366$$aLozano Albalate, María Teresa
000153003 700__ $$0(orcid)0000-0002-0690-3193$$aPelaez Coca, María Dolores
000153003 773__ $$g47 (2020), [4 pp.]$$pComput. cardiol.$$tComputing in Cardiology$$x2325-8861
000153003 85641 $$uhttps://cinc.org/archives/2020/$$zTexto completo de la revista
000153003 8564_ $$s893277$$uhttps://zaguan.unizar.es/record/153003/files/texto_completo.pdf$$yPostprint
000153003 8564_ $$s2586496$$uhttps://zaguan.unizar.es/record/153003/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000153003 909CO $$ooai:zaguan.unizar.es:153003$$particulos$$pdriver
000153003 951__ $$a2025-04-04-13:12:24
000153003 980__ $$aARTICLE