Unconstrained Estimation of HRV Indices after Removing Respiratory Influences from Heart Rate

Carolina Varon*, Jesus Lazaro, Juan Bolea, Alberto Hernando, Jordi Aguilo, Eduardo Gil, Sabine Van Huffel, Raquel Bailon

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

Objective: This paper proposes an approach to better estimate the sympathovagal balance (SB) and the respiratory sinus arrhythmia (RSA) after separating respiratory influences from the heart rate (HR). Methods: The separation is performed using orthogonal subspace projections and the approach is first tested using simulated HR and respiratory signals with different spectral properties. Then, RSA and SB are estimated during autonomic blockade and stress using the proposed approach and the classical heart rate variability (HRV) analysis. Both real- and ECG-derived respiration (EDR) are used and the reliability of the EDR is evaluated. Results: Mean absolute percentage errors lower than $\text{1}\%$ were obtained after removing previously known respiratory signals from simulated HR. The proposed indices were able to improve the quantification of SB during autonomic withdrawal. In the stress data, differences ($p< 0.003$) among relaxed and stressful phases were found with the proposed approach, using both the real respiration and the EDR, but they disappeared when using the classical HRV. Conclusion: A better assessment of the autonomic nervous system' response to pharmacological blockade and stress can be achieved after removing respiratory influences from HR, and this can be done using either the real respiration or the EDR. Significance: This work can be used to better identify vagal withdrawal and increased sympathetic activation when the classical HRV analysis fails due to the respiratory influences on HR. Furthermore, it can be computed using only the ECG, which is an advantage when developing wearable systems with limited number of sensors.

Original languageEnglish
Article number8555548
Pages (from-to)2386-2397
Number of pages12
JournalIEEE Journal of Biomedical and Health Informatics
Volume23
Issue number6
DOIs
Publication statusPublished - Nov 2019

Keywords

  • Respiratory sinus arrhythmia
  • stress
  • sympathovagal balance

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