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Multiple window coherence analysis of HRV power and respiratory frequency

Sandsten, Maria LU and Jönsson, Peter LU (2007) In IEEE Transactions on Biomedical Engineering 54(10). p.1770-1779
Abstract
In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, between the respiratory center frequency and the high-frequency band of the heart- rate variability (HRV) power. One aim is to examine whether a more restricted frequency range would better capture respiratory related HR variation, especially when the HR variation is changing rapidly. The respiratory peak is detected and a narrow-banded measure of the high-frequency (HF) band of the HRV is defined as the respiratory frequency plusmn0.05 Hz. We compare the mean square error of the correlation estimate between the frequency of the respiratory peak and the power of the HRV with the power in the usual 0.12-0.4 Hz frequency band. Different multiple... (More)
In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, between the respiratory center frequency and the high-frequency band of the heart- rate variability (HRV) power. One aim is to examine whether a more restricted frequency range would better capture respiratory related HR variation, especially when the HR variation is changing rapidly. The respiratory peak is detected and a narrow-banded measure of the high-frequency (HF) band of the HRV is defined as the respiratory frequency plusmn0.05 Hz. We compare the mean square error of the correlation estimate between the frequency of the respiratory peak and the power of the HRV with the power in the usual 0.12-0.4 Hz frequency band. Different multiple window spectrum techniques are used for the estimation of the respiratory frequency as well as for the power of the HRV. We compare the peak-matched multiple windows with the Welch method while evaluating the two different HF-power estimates mentioned above. The results show that using a more narrow band for the power estimation gives stronger correlation which indicates that the estimate of the power is more robust. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Correlation, covariance, heart-rate variability (HRV), peak-matched multiple windows (PM MWs), respiratory sinus arrhythmia (RSA), multiple-window spectrum analysis
in
IEEE Transactions on Biomedical Engineering
volume
54
issue
10
pages
1770 - 1779
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000249840500005
  • scopus:34548828233
ISSN
0018-9294
DOI
10.1109/TBME.2007.904527
language
English
LU publication?
yes
id
7bf81095-d337-4bb3-a148-a2e80fdbbb47 (old id 774532)
date added to LUP
2008-01-04 14:24:22
date last changed
2017-03-26 04:30:39
@article{7bf81095-d337-4bb3-a148-a2e80fdbbb47,
  abstract     = {In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, between the respiratory center frequency and the high-frequency band of the heart- rate variability (HRV) power. One aim is to examine whether a more restricted frequency range would better capture respiratory related HR variation, especially when the HR variation is changing rapidly. The respiratory peak is detected and a narrow-banded measure of the high-frequency (HF) band of the HRV is defined as the respiratory frequency plusmn0.05 Hz. We compare the mean square error of the correlation estimate between the frequency of the respiratory peak and the power of the HRV with the power in the usual 0.12-0.4 Hz frequency band. Different multiple window spectrum techniques are used for the estimation of the respiratory frequency as well as for the power of the HRV. We compare the peak-matched multiple windows with the Welch method while evaluating the two different HF-power estimates mentioned above. The results show that using a more narrow band for the power estimation gives stronger correlation which indicates that the estimate of the power is more robust.},
  author       = {Sandsten, Maria and Jönsson, Peter},
  issn         = {0018-9294},
  keyword      = {Correlation,covariance,heart-rate variability (HRV),peak-matched multiple windows (PM MWs),respiratory sinus arrhythmia (RSA),multiple-window spectrum analysis},
  language     = {eng},
  number       = {10},
  pages        = {1770--1779},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Transactions on Biomedical Engineering},
  title        = {Multiple window coherence analysis of HRV power and respiratory frequency},
  url          = {http://dx.doi.org/10.1109/TBME.2007.904527},
  volume       = {54},
  year         = {2007},
}