Respiratory rate estimation using respiratory sinus arrhythmia from photoplethysmography.

Respiratory rate estimation using respiratory sinus arrhythmia from photoplethysmography. Karlen, W., Brouse, C., J., Cooke, E., Ansermino, J., M., & Dumont, G., A. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 1201-4, 8, 2011.

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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.

@inproceedings{
 title = {Respiratory rate estimation using respiratory sinus arrhythmia from photoplethysmography.},
 type = {inproceedings},
 year = {2011},
 keywords = {anesthesia,heart rate variability,photo-plethysmogram,pulse oximeter,respiratory rate,respiratory sinus arrhythmia},
 pages = {1201-4},
 websites = {http://www.ncbi.nlm.nih.gov/pubmed/22254531},
 month = {8},
 city = {Boston},
 id = {b4e1a9b0-0979-3206-8821-7cbf19e89920},
 created = {2011-05-12T18:57:10.000Z},
 accessed = {2012-01-22},
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 last_modified = {2022-09-04T18:12:18.866Z},
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 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.},
 bibtype = {inproceedings},
 author = {Karlen, Walter and Brouse, Christopher J and Cooke, Erin and Ansermino, J Mark and Dumont, Guy A},
 doi = {10.1109/IEMBS.2011.6090282},
 booktitle = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}
}

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