Literature DB >> 22254531

Respiratory rate estimation using respiratory sinus arrhythmia from photoplethysmography.

Walter Karlen1, Christopher J Brouse, Erin Cooke, J Mark Ansermino, Guy A Dumont.   

Abstract

Respiratory rate (RR) is an important measurement for ambulatory care and there is high interest in its detection using unobtrusive mobile devices. For this study, we investigated the estimation of RR from a photoplethysmography (PPG) signal that originated from a pulse oximeter sensor and had a sub-optimal sampling rate. We explored the possibility of estimating RR by extracting respiratory sinus arrhythmia (RSA) from the PPG-derived heart rate variability (HRV) measurement using real-time algorithms. Data from 29 children and 13 adults undergoing general anesthesia were analyzed. We compared the RSA power derived from electrocardiography (ECG) with PPG at the reference RR derived from capnography. The power of the PPG was significantly higher than that of the ECG (182.42 ± 36.75 dB vs. 162.30 ± 43.66 dB). Further, the mean RR error for PPG was lower than ECG. Both PPG and ECG RR estimation techniques were more powerful and reliable in cases of spontaneous ventilation than when pressure controlled ventilation was used. The analysis of cases containing artifacts in the PPG revealed a significant increase in RR error, a trend that was less pronounced for controlled ventilation. These results indicate that the estimation of RR from the sub-optimally sampled PPG signal is possible and more reliable than from the ECG.

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Year:  2011        PMID: 22254531     DOI: 10.1109/IEMBS.2011.6090282

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Implementing Mobile HRV Biofeedback as Adjunctive Therapy During Inpatient Psychiatric Rehabilitation Facilitates Recovery of Depressive Symptoms and Enhances Autonomic Functioning Short-Term: A 1-Year Pre-Post-intervention Follow-Up Pilot Study.

Authors:  Josef M Tatschl; Sigurd M Hochfellner; Andreas R Schwerdtfeger
Journal:  Front Neurosci       Date:  2020-07-21       Impact factor: 4.677

Review 2.  Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.

Authors:  Peter H Charlton; Drew A Birrenkott; Timothy Bonnici; Marco A F Pimentel; Alistair E W Johnson; Jordi Alastruey; Lionel Tarassenko; Peter J Watkinson; Richard Beale; David A Clifton
Journal:  IEEE Rev Biomed Eng       Date:  2017-10-24

3.  Estimating respiratory and heart rates from the correntropy spectral density of the photoplethysmogram.

Authors:  Ainara Garde; Walter Karlen; J Mark Ansermino; Guy A Dumont
Journal:  PLoS One       Date:  2014-01-22       Impact factor: 3.240

Review 4.  Advances in Photopletysmography Signal Analysis for Biomedical Applications.

Authors:  Jermana L Moraes; Matheus X Rocha; Glauber G Vasconcelos; José E Vasconcelos Filho; Victor Hugo C de Albuquerque; Auzuir R Alexandria
Journal:  Sensors (Basel)       Date:  2018-06-09       Impact factor: 3.576

  4 in total

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