A Fully Automated Algorithm for the Determination of Respiratory Rate from the Photoplethysmogram

Overview

Journal J Clin Monit Comput

Publisher Springer

Specialties Anesthesiology
General Medicine
Medical Informatics

Date 2006 Mar 15

PMID 16532280

Citations 10

Authors

Paul A Leonard

J Graham Douglas

Neil R Grubb

David Clifton

Paul S Addison

James N Watson

Affiliations

Soon will be listed here.

Abstract

Objective: To determine if an automatic algorithm using wavelet analysis techniques can be used to reliably determine respiratory rate from the photoplethysmogram (PPG).

Methods: Photoplethysmograms were obtained from 12 spontaneously breathing healthy adult volunteers. Three related wavelet transforms were automatically polled to obtain a measure of respiratory rate. This was compared with a secondary timing signal obtained by asking the volunteers to actuate a small push button switch, held in their right hand, in synchronisation with their respiration. In addition, individual breaths were resolved using the wavelet-method to identify the source of any discrepancies.

Results: Volunteer respiratory rates varied from 6.56 to 18.89 breaths per minute. Through training of the algorithm it was possible to determine a respiratory rate for all 12 traces acquired during the study. The maximum error between the PPG derived rates and the manually determined rate was found to be 7.9%.

Conclusion: Our technique allows the accurate measurement of respiratory rate from the photoplethysmogram, and leads the way for developing a simple non-invasive combined respiration and saturation monitor.

Citing Articles

The use of successive systolic differences in photoplethysmographic (PPG) signals for respiratory rate estimation.

Arguello-Prada E, Marcillo Ibarra K, Diaz Jimenez K Heliyon. 2024; 10(4):e26036.

PMID: 38370197 PMC: 10869914. DOI: 10.1016/j.heliyon.2024.e26036.

A Single-Center Validation of the Accuracy of a Photoplethysmography-Based Smartwatch for Screening Obstructive Sleep Apnea.

Chen Y, Wang W, Guo Y, Zhang H, Chen Y, Xie L Nat Sci Sleep. 2021; 13:1533-1544.

PMID: 34557047 PMC: 8453177. DOI: 10.2147/NSS.S323286.

Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization.

Lei R, Ling B, Feng P, Chen J Sensors (Basel). 2020; 20(11).

PMID: 32517226 PMC: 7309083. DOI: 10.3390/s20113238.

Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.

Charlton P, Birrenkott D, Bonnici T, Pimentel M, Johnson A, Alastruey J IEEE Rev Biomed Eng. 2018; 11:2-20.

PMID: 29990026 PMC: 7612521. DOI: 10.1109/RBME.2017.2763681.

A Brief Review of Non-invasive Monitoring of Respiratory Condition for Extubated Patients with or at Risk for Obstructive Sleep Apnea after Surgery.

Zhang X, Kassem M, Zhou Y, Shabsigh M, Wang Q, Xu X Front Med (Lausanne). 2017; 4:26.

PMID: 28337439 PMC: 5340767. DOI: 10.3389/fmed.2017.00026.

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