A robust method for ECG-Based estimation of the respiratory frequency during stress testing
(2006) In IEEE Transactions on Biomedical Engineering 53(7). p.1273-1285- Abstract
- A robust method is presented for electrocardiogram (ECG)-based estimation of the respiratory frequency during stress testing. Such ECGs contain highly nonstationary noise and exhibit changes in QRS morphology which, when combined with the dynamic nature of the respiratory frequency, make most existing methods break down. The present method exploits the oscillatory pattern of the rotation angles of the heart's electrical axis as induced by respiration. The series of rotation angles, obtained from least-squares loop alignment, is subject to power spectral analysis and estimation of the respiratory frequency. Robust techniques are introduced to handle the nonstationary properties of exercise ECGs. The method is evaluated by means of both... (More)
- A robust method is presented for electrocardiogram (ECG)-based estimation of the respiratory frequency during stress testing. Such ECGs contain highly nonstationary noise and exhibit changes in QRS morphology which, when combined with the dynamic nature of the respiratory frequency, make most existing methods break down. The present method exploits the oscillatory pattern of the rotation angles of the heart's electrical axis as induced by respiration. The series of rotation angles, obtained from least-squares loop alignment, is subject to power spectral analysis and estimation of the respiratory frequency. Robust techniques are introduced to handle the nonstationary properties of exercise ECGs. The method is evaluated by means of both simulated signals, and ECG/airflow signals recorded from 14 volunteers and 20 patients during stress testing. The resulting respiratory frequency estimation error is, for simulated signals, equal to 0.5% +/- 0.2%, mean SD (0.002 +/- 0.001 Hz), whereas the error between respiratory frequencies of the ECG-derived method and the airflow signals is 5.9 % +/- 4 % (0.022 +/- 0.016 Hz). The results suggest that the method is highly suitable for analysis of noisy ECG signals recorded during stress testing. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/404541
- author
- Bailon, R ; Sörnmo, Leif LU and Laguna, P
- organization
- publishing date
- 2006
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- robustness, signal synthesis, repiratory system, respiratory frequency, exercise, ECG-derived respiration (EDR), electrocardiography
- in
- IEEE Transactions on Biomedical Engineering
- volume
- 53
- issue
- 7
- pages
- 1273 - 1285
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000238711600007
- scopus:33746855128
- pmid:16830932
- ISSN
- 1558-2531
- DOI
- 10.1109/TBME.2006.871888
- language
- English
- LU publication?
- yes
- id
- 1c3b5b84-ce5c-458d-8d4c-1c6d3d9b3131 (old id 404541)
- date added to LUP
- 2016-04-01 17:01:28
- date last changed
- 2022-03-22 22:45:32
@article{1c3b5b84-ce5c-458d-8d4c-1c6d3d9b3131,
abstract = {{A robust method is presented for electrocardiogram (ECG)-based estimation of the respiratory frequency during stress testing. Such ECGs contain highly nonstationary noise and exhibit changes in QRS morphology which, when combined with the dynamic nature of the respiratory frequency, make most existing methods break down. The present method exploits the oscillatory pattern of the rotation angles of the heart's electrical axis as induced by respiration. The series of rotation angles, obtained from least-squares loop alignment, is subject to power spectral analysis and estimation of the respiratory frequency. Robust techniques are introduced to handle the nonstationary properties of exercise ECGs. The method is evaluated by means of both simulated signals, and ECG/airflow signals recorded from 14 volunteers and 20 patients during stress testing. The resulting respiratory frequency estimation error is, for simulated signals, equal to 0.5% +/- 0.2%, mean SD (0.002 +/- 0.001 Hz), whereas the error between respiratory frequencies of the ECG-derived method and the airflow signals is 5.9 % +/- 4 % (0.022 +/- 0.016 Hz). The results suggest that the method is highly suitable for analysis of noisy ECG signals recorded during stress testing.}},
author = {{Bailon, R and Sörnmo, Leif and Laguna, P}},
issn = {{1558-2531}},
keywords = {{robustness; signal synthesis; repiratory system; respiratory frequency; exercise; ECG-derived respiration (EDR); electrocardiography}},
language = {{eng}},
number = {{7}},
pages = {{1273--1285}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Biomedical Engineering}},
title = {{A robust method for ECG-Based estimation of the respiratory frequency during stress testing}},
url = {{http://dx.doi.org/10.1109/TBME.2006.871888}},
doi = {{10.1109/TBME.2006.871888}},
volume = {{53}},
year = {{2006}},
}