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Extraction of respiratory signals from the electrocardiogram and photoplethysmogram: technical and physiological determinants.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Charlton, Peter H 
Bonnici, Timothy 
Tarassenko, Lionel 
Alastruey, Jordi 
Clifton, David A 

Abstract

OBJECTIVE: Breathing rate (BR) can be estimated by extracting respiratory signals from the electrocardiogram (ECG) or photoplethysmogram (PPG). The extracted respiratory signals may be influenced by several technical and physiological factors. In this study, our aim was to determine how technical and physiological factors influence the quality of respiratory signals. APPROACH: Using a variety of techniques 15 respiratory signals were extracted from the ECG, and 11 from PPG signals collected from 57 healthy subjects. The quality of each respiratory signal was assessed by calculating its correlation with a reference oral-nasal pressure respiratory signal using Pearson's correlation coefficient. MAIN RESULTS: Relevant results informing device design and clinical application were obtained. The results informing device design were: (i) seven out of 11 respiratory signals were of higher quality when extracted from finger PPG compared to ear PPG; (ii) laboratory equipment did not provide higher quality of respiratory signals than a clinical monitor; (iii) the ECG provided higher quality respiratory signals than the PPG; (iv) during downsampling of the ECG and PPG significant reductions in quality were first observed at sampling frequencies of  <250 Hz and  <16 Hz respectively. The results informing clinical application were: (i) frequency modulation-based respiratory signals were generally of lower quality in elderly subjects compared to young subjects; (ii) the qualities of 23 out of 26 respiratory signals were reduced at elevated BRs; (iii) there were no differences associated with gender. SIGNIFICANCE: Recommendations based on the results are provided regarding device designs for BR estimation, and clinical applications. The dataset and code used in this study are publicly available.

Description

Keywords

Adolescent, Adult, Aged, Aging, Electrocardiography, Female, Humans, Male, Photoplethysmography, Respiration, Respiratory Rate, Sex Characteristics, Signal Processing, Computer-Assisted, Young Adult

Journal Title

Physiol Meas

Conference Name

Journal ISSN

0967-3334
1361-6579

Volume Title

38

Publisher

IOP Publishing