Heart rate variability metrics for fine-grained stress level assessment

Detalhes bibliográficos
Autor(a) principal: Pereira,T
Data de Publicação: 2017
Outros Autores: Almeida,PR, João Paulo Cunha, Aguiar,A
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/6356
http://dx.doi.org/10.1016/j.cmpb.2017.06.018
Resumo: Background and Objectives: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. Methods: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacketml while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. Results: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. Conclusions: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.
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spelling Heart rate variability metrics for fine-grained stress level assessmentBackground and Objectives: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. Methods: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacketml while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. Results: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. Conclusions: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.2018-01-16T12:41:00Z2017-01-01T00:00:00Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6356http://dx.doi.org/10.1016/j.cmpb.2017.06.018engPereira,TAlmeida,PRJoão Paulo CunhaAguiar,Ainfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:08Zoai:repositorio.inesctec.pt:123456789/6356Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:43.347068Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Heart rate variability metrics for fine-grained stress level assessment
title Heart rate variability metrics for fine-grained stress level assessment
spellingShingle Heart rate variability metrics for fine-grained stress level assessment
Pereira,T
title_short Heart rate variability metrics for fine-grained stress level assessment
title_full Heart rate variability metrics for fine-grained stress level assessment
title_fullStr Heart rate variability metrics for fine-grained stress level assessment
title_full_unstemmed Heart rate variability metrics for fine-grained stress level assessment
title_sort Heart rate variability metrics for fine-grained stress level assessment
author Pereira,T
author_facet Pereira,T
Almeida,PR
João Paulo Cunha
Aguiar,A
author_role author
author2 Almeida,PR
João Paulo Cunha
Aguiar,A
author2_role author
author
author
dc.contributor.author.fl_str_mv Pereira,T
Almeida,PR
João Paulo Cunha
Aguiar,A
description Background and Objectives: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. Methods: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacketml while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. Results: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. Conclusions: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01T00:00:00Z
2017
2018-01-16T12:41:00Z
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http://dx.doi.org/10.1016/j.cmpb.2017.06.018
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http://dx.doi.org/10.1016/j.cmpb.2017.06.018
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