Effects of Age, BMI, anxiety and stress on the parameters of a stochastic model for heart rate variability including respiratory information

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

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 considering 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 parameters with age, BMI, State and Trait Anxiety as well as stress level.

Details

Authors
Organisations
External organisations
  • Kristianstad University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Signal Processing
  • Medical Laboratory and Measurements Technologies

Keywords

  • Chirp Respiratory Frequency, HRV, Linear, Locally Stationary Chirp Processes, Logistic Regression, Time-series Modelling, Time-varying Signals
Original languageEnglish
Title of host publicationBIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
PublisherSciTePress
Pages17-25
Number of pages9
Volume4
ISBN (Electronic)9789897582790
Publication statusPublished - 2018
Publication categoryResearch
Peer-reviewedYes
Event11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018 - Funchal, Madeira, Portugal
Duration: 2018 Jan 192018 Jan 21

Conference

Conference11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
CountryPortugal
CityFunchal, Madeira
Period2018/01/192018/01/21