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Effects of age, BMI, anxiety and stress on the parameters of a stochastic model for heart rate variability including respiratory information
Lund University.
Kristianstad University, Faculty of Education, Avdelningen för psykologi.ORCID iD: 0000-0002-2921-3945
Lund University.
2018 (English)In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, SCITEPRESS , 2018, Vol. 4, p. 17-25Conference paper, Published paper (Refereed)
Abstract [en]

Recent studies have focused on investigating different factors that may affect heart rate variability (HRV),pointing especially to the effects of age, gender and stress level. Other findings raise the importance of consid- ering the respiratory frequency in the analysis of HRV signals. In this study, we evaluate the effect of several covariates on the parameters of a stochastic model for HRV. The data was recorded from 47 test participants, whose breathing was controlled by following a metronome with increasing frequency. This setup allows for a controlled acquisition of respiratory related HRV data covering the frequency range in which adults breathe in different everyday situations. A stochastic model, known as Locally Stationary Chirp Process, accounts for the respiratory signal information and models the HRV data. The model parameters are estimated with a novel inference method based on the separability features possessed by the process covariance function. Least square regression analysis using several available covariates is used to investigate the correlation with the stochastic model parameters. The results show statistically significant correlation of the model parameterswith age, BMI, State and Trait Anxiety as well as stress level.

Place, publisher, year, edition, pages
SCITEPRESS , 2018. Vol. 4, p. 17-25
Keywords [en]
HRV, Chirp Respiratory Frequency, Locally Stationary Chirp Processes, Time-varying Signals, Time-series
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:hkr:diva-17891DOI: 10.5220/0006512900170025ISBN: 978-989-758-279-0 (print)OAI: oai:DiVA.org:hkr-17891DiVA, id: diva2:1185778
Conference
BIOSTEC 2018
Available from: 2018-02-26 Created: 2018-02-26 Last updated: 2018-02-26Bibliographically approved

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Total: 54 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf