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Authors: Rachele Anderson 1 ; Peter Jönsson 2 and Maria Sandsten 1

Affiliations: 1 Centre for Mathematical Sciences and Lund University, Sweden ; 2 School of Education and Environment, Centre for Psychology and Kristianstad University, Sweden

ISBN: 978-989-758-279-0

Keyword(s): HRV, Chirp Respiratory Frequency, Locally Stationary Chirp Processes, Time-varying Signals, Time-series Modelling, Linear and Logistic Regression.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics

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 regressio n 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. (More)

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Paper citation in several formats:
Anderson R., Jönsson P. and Sandsten M. (2018). Effects of Age, BMI, Anxiety and Stress on the Parameters of a Stochastic Model for Heart Rate Variability Including Respiratory Information.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS, ISBN 978-989-758-279-0, pages 17-25. DOI: 10.5220/0006512900170025

@conference{biosignals18,
author={Rachele Anderson and Peter Jönsson and Maria Sandsten},
title={Effects of Age, BMI, Anxiety and Stress on the Parameters of a Stochastic Model for Heart Rate Variability Including Respiratory Information},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS,},
year={2018},
pages={17-25},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006512900170025},
isbn={978-989-758-279-0},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS,
TI - Effects of Age, BMI, Anxiety and Stress on the Parameters of a Stochastic Model for Heart Rate Variability Including Respiratory Information
SN - 978-989-758-279-0
AU - Anderson R.
AU - Jönsson P.
AU - Sandsten M.
PY - 2018
SP - 17
EP - 25
DO - 10.5220/0006512900170025

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