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Electrocardiogram derived respiration from QRS slopes : Evaluation with stress testing recordings

Lazaro, Jesus ; Alcaine, Alejandro ; Romero, Daniel ; Gil, Eduardo ; Laguna, Pablo ; Sornmo, Leif LU and Bailon, Raquel (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
; ; ; ; ; and
organization
publishing date
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
2025-10-14 11:09:21
@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}},
}