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Insights on Spectral Measures for HRV Based on a Novel Approach for Data Acquisition

Anderson, Rachele LU orcid ; Jönsson, Peter and Sandsten, Maria LU (2018) In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 2018. p.510-513
Abstract

In this paper, we present new insights on classical spectral measures for heart rate variability (HRV), based on a novel method for HRV acquisition. A dynamic breathing task, where the test participants are asked to breathe following a metronome with slowly increasing frequency, allows for the acquisition of respiratory-related HRV-data covering the frequency range in which adults breathe in different everyday situations. We discuss how the use of a time-frequency representation, e.g. the spectrogram or the Wigner-Ville distribution, should be preferred to the traditional use of the periodogram, due to the non-stationarity of the data. We argue that this approach can highlight the correlation of spectral measures such as low-frequency... (More)

In this paper, we present new insights on classical spectral measures for heart rate variability (HRV), based on a novel method for HRV acquisition. A dynamic breathing task, where the test participants are asked to breathe following a metronome with slowly increasing frequency, allows for the acquisition of respiratory-related HRV-data covering the frequency range in which adults breathe in different everyday situations. We discuss how the use of a time-frequency representation, e.g. the spectrogram or the Wigner-Ville distribution, should be preferred to the traditional use of the periodogram, due to the non-stationarity of the data. We argue that this approach can highlight the correlation of spectral measures such as low-frequency and high-frequency HRV with relevant factors as age, gender and Body-Mass-Index, thanks to the improved quality of the spectral measures.

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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Heart rate variability, Time-Frequency Analysis, Spectrogram, Wigner-Ville distribution
in
Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
volume
2018
pages
4 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85056638579
  • pmid:30440446
ISSN
1557-170X
DOI
10.1109/EMBC.2018.8512423
language
English
LU publication?
yes
id
5c7c7caf-f248-4121-a9ea-fbfa55bb06e8
date added to LUP
2018-12-16 19:17:39
date last changed
2021-09-22 05:35:19
@article{5c7c7caf-f248-4121-a9ea-fbfa55bb06e8,
  abstract     = {<p>In this paper, we present new insights on classical spectral measures for heart rate variability (HRV), based on a novel method for HRV acquisition. A dynamic breathing task, where the test participants are asked to breathe following a metronome with slowly increasing frequency, allows for the acquisition of respiratory-related HRV-data covering the frequency range in which adults breathe in different everyday situations. We discuss how the use of a time-frequency representation, e.g. the spectrogram or the Wigner-Ville distribution, should be preferred to the traditional use of the periodogram, due to the non-stationarity of the data. We argue that this approach can highlight the correlation of spectral measures such as low-frequency and high-frequency HRV with relevant factors as age, gender and Body-Mass-Index, thanks to the improved quality of the spectral measures.</p>},
  author       = {Anderson, Rachele and Jönsson, Peter and Sandsten, Maria},
  issn         = {1557-170X},
  language     = {eng},
  pages        = {510--513},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  series       = {Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings},
  title        = {Insights on Spectral Measures for HRV Based on a Novel Approach for Data Acquisition},
  url          = {http://dx.doi.org/10.1109/EMBC.2018.8512423},
  doi          = {10.1109/EMBC.2018.8512423},
  volume       = {2018},
  year         = {2018},
}