Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component

This study’s primary objective was to identify individuals whose physiological responses deviated from the rest of the study population by automatically monitoring atmospheric pressure levels to which they are exposed and using parameters derived from their heart rate variability (HRV). To achieve t...

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Autores: Peláez-Coca, María Dolores, Hernando, Alberto, Lozano, María Teresa, Bolea, Juan, Izquierdo, David, Sánchez, Carlos
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Recursos:Universidad de Zaragoza
Repositorio:Zaguán. Repositorio Digital de la Universidad de Zaragoza
OAI Identifier:oai:zaguan.unizar.es:130424
Acesso em linha:http://zaguan.unizar.es/record/130424
Access Level:acceso abierto
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spelling Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory ComponentPeláez-Coca, María DoloresHernando, AlbertoLozano, María TeresaBolea, JuanIzquierdo, DavidSánchez, CarlosThis study’s primary objective was to identify individuals whose physiological responses deviated from the rest of the study population by automatically monitoring atmospheric pressure levels to which they are exposed and using parameters derived from their heart rate variability (HRV). To achieve this, 28 volunteers were placed in a dry hyperbaric chamber, where they experienced varying pressures from 1 to 5 atmospheres, with five sequential stops lasting five minutes each at different atmospheric pressures. The HRV was dissected into two components: the respiratory component, which is linked to respiration; and the residual component, which is influenced by factors beyond respiration. Nine parameters were assessed, including the respiratory rate, four classic HRV temporal parameters, and four frequency parameters. A k-nearest neighbors classifier based on cosine distance successfully identified the atmospheric pressures to which the subjects were exposed to. The classifier achieved an 88.5% accuracy rate in distinguishing between the 5 atm and 3 atm stages using only four features: respiratory rate, heart rate, and two frequency parameters associated with the subjects’ sympathetic responses. Furthermore, the study identified 6 out of 28 subjects as having atypical responses across all pressure levels when compared to the majority. Interestingly, two of these subjects stood out in terms of gender and having less prior diving experience, but they still exhibited normal responses to immersion. This suggests the potential for establishing distinct safety protocols for divers based on their previous experience and gender.2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://zaguan.unizar.es/record/130424reponame:Zaguán. Repositorio Digital de la Universidad de Zaragozainstname:Universidad de ZaragozaInglésinfo:eu-repo/semantics/openAccessoai:zaguan.unizar.es:1304242026-05-29T13:59:51Z
dc.title.none.fl_str_mv Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
title Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
spellingShingle Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
Peláez-Coca, María Dolores
title_short Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
title_full Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
title_fullStr Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
title_full_unstemmed Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
title_sort Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
dc.creator.none.fl_str_mv Peláez-Coca, María Dolores
Hernando, Alberto
Lozano, María Teresa
Bolea, Juan
Izquierdo, David
Sánchez, Carlos
author Peláez-Coca, María Dolores
author_facet Peláez-Coca, María Dolores
Hernando, Alberto
Lozano, María Teresa
Bolea, Juan
Izquierdo, David
Sánchez, Carlos
author_role author
author2 Hernando, Alberto
Lozano, María Teresa
Bolea, Juan
Izquierdo, David
Sánchez, Carlos
author2_role author
author
author
author
author
description This study’s primary objective was to identify individuals whose physiological responses deviated from the rest of the study population by automatically monitoring atmospheric pressure levels to which they are exposed and using parameters derived from their heart rate variability (HRV). To achieve this, 28 volunteers were placed in a dry hyperbaric chamber, where they experienced varying pressures from 1 to 5 atmospheres, with five sequential stops lasting five minutes each at different atmospheric pressures. The HRV was dissected into two components: the respiratory component, which is linked to respiration; and the residual component, which is influenced by factors beyond respiration. Nine parameters were assessed, including the respiratory rate, four classic HRV temporal parameters, and four frequency parameters. A k-nearest neighbors classifier based on cosine distance successfully identified the atmospheric pressures to which the subjects were exposed to. The classifier achieved an 88.5% accuracy rate in distinguishing between the 5 atm and 3 atm stages using only four features: respiratory rate, heart rate, and two frequency parameters associated with the subjects’ sympathetic responses. Furthermore, the study identified 6 out of 28 subjects as having atypical responses across all pressure levels when compared to the majority. Interestingly, two of these subjects stood out in terms of gender and having less prior diving experience, but they still exhibited normal responses to immersion. This suggests the potential for establishing distinct safety protocols for divers based on their previous experience and gender.
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://zaguan.unizar.es/record/130424
url http://zaguan.unizar.es/record/130424
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv
publisher.none.fl_str_mv
dc.source.none.fl_str_mv reponame:Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname:Universidad de Zaragoza
instname_str Universidad de Zaragoza
reponame_str Zaguán. Repositorio Digital de la Universidad de Zaragoza
collection Zaguán. Repositorio Digital de la Universidad de Zaragoza
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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