Extraction of Respiratory Signals from the ECG and PPG

Summary

In this article the toolbox (v.3) was used to assess the influences of a range of technical and physiological factors on respiratory signals extracted from the ECG and PPG. Respiratory signals were extracted from the Vortal dataset (young and elderly subjects) using a wide range of techniques. The correlations of each extracted respiratory signal with a reference respiratory signal were calculated. This allowed us to investigate the effect of several technical factors (including site of PPG measurement, type of recording equipment, input signal (ECG or PPG) and sampling frequency), and physiological factors (including age, gender and respiratory rate) on the respiratory signals.

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.

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Accompanying presentation

This presentation provides an overview of the article. It is designed for use in journal club settings, and was originally presented at the University of Oxford. DOI: 10.5281/zenodo.400255

Replicating this study