Electrocardiogram derived respiration from QRS slopes : Evaluation with stress testing recordings
(2013) 2013 40th Computing in Cardiology Conference, CinC 2013 40. p.655-658- Abstract
A method for respiratory rate estimation from electrocardiogram (ECG), based on variations in QRS complexes slopes, is evaluated over stress testing recordings. Besides the 12 standard, and the 3 vectorcardiogram (VCG), 2 additional leads derived from the VCG are analyzed. A total of 34 slope series were studied, 2 for each lead: slopes between the peaks of the Q and R waves, and between the peaks of the R and S waves. Respiratory rate is estimated by using a time-frequency based algorithm which can combine information from several derived respiration signals. Evaluation was performed over a database containing ECG and respiratory signals simultaneously recorded from 30 subjects spontaneously breathing during a stress test. Respiratory... (More)
A method for respiratory rate estimation from electrocardiogram (ECG), based on variations in QRS complexes slopes, is evaluated over stress testing recordings. Besides the 12 standard, and the 3 vectorcardiogram (VCG), 2 additional leads derived from the VCG are analyzed. A total of 34 slope series were studied, 2 for each lead: slopes between the peaks of the Q and R waves, and between the peaks of the R and S waves. Respiratory rate is estimated by using a time-frequency based algorithm which can combine information from several derived respiration signals. Evaluation was performed over a database containing ECG and respiratory signals simultaneously recorded from 30 subjects spontaneously breathing during a stress test. Respiratory rate estimation is performed with information of 4 different combinations of QRS slope series. The best results in respiratory rate estimation error terms are -1.07 ± 8.86% (-11.47 ± 37.97 mHz). These results suggest that proposed methods based on QRS slopes are highly suitable for respiratory rate estimation from ECG signal, specially at very non-stationary and noise scenarios as stress test.
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- author
- Lazaro, Jesus ; Alcaine, Alejandro ; Romero, Daniel ; Gil, Eduardo ; Laguna, Pablo ; Sornmo, Leif LU and Bailon, Raquel
- organization
- publishing date
- 2013-12-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2013 Computing in Cardiology
- volume
- 40
- article number
- 6713462
- pages
- 4 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2013 40th Computing in Cardiology Conference, CinC 2013
- conference location
- Zaragoza, Spain
- conference dates
- 2013-09-22 - 2013-09-25
- external identifiers
-
- scopus:84894165745
- ISBN
- 9781479908844
- language
- English
- LU publication?
- yes
- id
- 3b5f20d8-9e4d-4b21-b0cd-bd8c00712860
- alternative location
- https://ieeexplore.ieee.org/document/6713462
- date added to LUP
- 2019-06-04 15:45:02
- date last changed
- 2022-01-31 21:25:50
@inproceedings{3b5f20d8-9e4d-4b21-b0cd-bd8c00712860, abstract = {{<p>A method for respiratory rate estimation from electrocardiogram (ECG), based on variations in QRS complexes slopes, is evaluated over stress testing recordings. Besides the 12 standard, and the 3 vectorcardiogram (VCG), 2 additional leads derived from the VCG are analyzed. A total of 34 slope series were studied, 2 for each lead: slopes between the peaks of the Q and R waves, and between the peaks of the R and S waves. Respiratory rate is estimated by using a time-frequency based algorithm which can combine information from several derived respiration signals. Evaluation was performed over a database containing ECG and respiratory signals simultaneously recorded from 30 subjects spontaneously breathing during a stress test. Respiratory rate estimation is performed with information of 4 different combinations of QRS slope series. The best results in respiratory rate estimation error terms are -1.07 ± 8.86% (-11.47 ± 37.97 mHz). These results suggest that proposed methods based on QRS slopes are highly suitable for respiratory rate estimation from ECG signal, specially at very non-stationary and noise scenarios as stress test.</p>}}, author = {{Lazaro, Jesus and Alcaine, Alejandro and Romero, Daniel and Gil, Eduardo and Laguna, Pablo and Sornmo, Leif and Bailon, Raquel}}, booktitle = {{2013 Computing in Cardiology}}, isbn = {{9781479908844}}, language = {{eng}}, month = {{12}}, pages = {{655--658}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Electrocardiogram derived respiration from QRS slopes : Evaluation with stress testing recordings}}, url = {{https://ieeexplore.ieee.org/document/6713462}}, volume = {{40}}, year = {{2013}}, }