69982 20221020131653.0 doi 10.1109/JBHI.2018.2797982 sideral 105486 ART-2019-105486 eng Hernando, Alberto (orcid)0000-0003-2596-7237 Autonomic nervous system measurement in hyperbaric environments using ECG and PPG signals 2019 Access copy available to the general public Unrestricted The main aim of this work was to characterise the Autonomic Nervous System (ANS) response in hyper- baric environments using electrocardiogram (ECG) and pulse- photoplethysmogram (PPG) signals. To that end, 26 subjects were introduced into a hyperbaric chamber and five stages with different atmospheric pressures (1 atm; descent to 3 and 5 atm; ascent to 3 and 1 atm) were recorded. Respiratory information was extracted from the ECG and PPG signals and a combined respiratory rate was studied. This information was also used to analyse Heart Rate Variability (HRV) and Pulse Rate Variability (PRV). The database was cleaned by eliminating those cases where the respiratory rate dropped into the low frequency band (LF: 0.04-0.15 Hz) and those in which there was a discrepancy between the respiratory rates estimated using the ECG and PPG signals. Classical temporal and frequency indices were calculated in such cases. The ECG results showed a time-related depen- dency, with the heart rate and sympathetic markers (normalised power in LF and LF/HF ratio) decreasing as more time was spent inside the hyperbaric environment. A dependency between the atmospheric pressure and the parasympathetic response, as reflected in the high frequency band power (HF: 0.15-0.40 Hz), was also found, with power increasing with atmospheric pressure. The combined respiratory rate also reached a maximum in the deepest stage, thus highlighting a significant difference between this stage and the first one. The PPG data gave similar findings and also allowed the oxygen saturation to be computed, therefore we propose the use of this signal for future studies in hyperbaric environments. info:eu-repo/grantAgreement/ES/DGA/T04 info:eu-repo/grantAgreement/EC/H2020/745755/EU/Wearable Cardiorespiratory Monitor/WECARMON This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 745755-WECARMON info:eu-repo/grantAgreement/ES/MINECO/TEC2014-54143-P info:eu-repo/grantAgreement/ES/MINECO/TIN2014-5356-R info:eu-repo/grantAgreement/ES/UZ/CUD2013-11 info:eu-repo/grantAgreement/ES/UZ/CUD2016-TEC-03 info:eu-repo/grantAgreement/ES/UZ/CUD2016-TEC-04 info:eu-repo/grantAgreement/ES/UZ/CUD2016-18 info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 5.223 2019 COMPUTER SCIENCE, INFORMATION SYSTEMS 15 / 156 = 0.096 2019 Q1 T1 MATHEMATICAL & COMPUTATIONAL BIOLOGY 5 / 59 = 0.085 2019 Q1 T1 MEDICAL INFORMATICS 1 / 27 = 0.037 2019 Q1 T1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 12 / 109 = 0.11 2019 Q1 T1 1.306 2019 Biotechnology 2019 Q1 Health Information Management 2019 Q1 Electrical and Electronic Engineering 2019 Q1 Computer Science Applications 2019 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Peláez-Coca, María Dolores (orcid)0000-0002-0690-3193 Lozano, María Teresa (orcid)0000-0003-0630-4366 Aiger, Monserrat Universidad de Zaragoza (orcid)0000-0002-8953-0600 Izquierdo, David (orcid)0000-0002-4746-3139 Sánchez, Alberto (orcid)0000-0002-4434-2630 López-Jurado, María Isabel Moura, Ignacio Fidalgo, Joaquín Lázaro, Jesús Universidad de Zaragoza (orcid)0000-0001-8742-0072 Gil, Eduardo Universidad de Zaragoza (orcid)0000-0001-7285-0715 4009 740 Universidad de Zaragoza Dpto. Psicología y Sociología Área Psicología Social 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 23, 1 (2019), 132-142 IEEE j. biomed. health inform. IEEE journal of biomedical and health informatics 2168-2194 298725 http://zaguan.unizar.es/record/69982/files/texto_completo.pdf Postprint 142256 http://zaguan.unizar.es/record/69982/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:69982 articulos driver 2022-10-20-13:05:22 ARTICLE