Skip to main content
Top
Published in: Journal of Clinical Monitoring and Computing 1/2012

Open Access 01-02-2012

Developing an algorithm for pulse oximetry derived respiratory rate (RRoxi): a healthy volunteer study

Authors: Paul S. Addison, James N. Watson, Michael L. Mestek, Roger S. Mecca

Published in: Journal of Clinical Monitoring and Computing | Issue 1/2012

Login to get access

Abstract

Objective The presence of respiratory information within the pulse oximeter signal (PPG) is a well-documented phenomenon. However, extracting this information for the purpose of continuously monitoring respiratory rate requires: (1) the recognition of the multi-faceted manifestations of respiratory modulation components within the PPG and the complex interactions among them; (2) the implementation of appropriate advanced signal processing techniques to take full advantage of this information; and (3) the post-processing infrastructure to deliver a clinically useful reported respiratory rate to the end user. A holistic algorithmic approach to the problem is therefore required. We have developed the RROXI algorithm based on this principle and its performance on healthy subject trial data is described herein.
Methods Finger PPGs were collected from a cohort of 139 healthy adult volunteers monitored during free breathing over an 8-min period. These were subsequently processed using a novel in-house algorithm based on continuous wavelet transform technology within an infrastructure incorporating weighted averaging and logical decision making processes. The computed oximeter respiratory rates (RRoxi) were then compared to an end-tidal CO2 reference rate (\( {\text{RR}}_{{{\text{ETCO}}_{ 2} }} \)).
Results \( {\text{RR}}_{{{\text{ETCO}}_{ 2} }} \) ranged from a lowest recorded value of 2.97 breaths per min (br/min) to a highest value of 28.02 br/min. The mean rate was 14.49 br/min with standard deviation of 4.36 br/min. Excellent agreement was found between RRoxi and \( {\text{RR}}_{{{\text{ETCO}}_{ 2} }} \), with a mean difference of −0.23 br/min and standard deviation of 1.14 br/min. The two measures are tightly spread around the line of agreement with a strong correlation observable between them (R 2 = 0.93).
Conclusions These data indicate that RRoxi represents a viable technology for the measurement of respiratory rate of healthy individuals.
Literature
1.
go back to reference Addison PS. The illustrated wavelet transform handbook. New York: Taylor & Francis; 2002.CrossRef Addison PS. The illustrated wavelet transform handbook. New York: Taylor & Francis; 2002.CrossRef
2.
go back to reference Chon KH, Dash S, Ju K. Estimation of respiratory rate from photoplethysmogram data using time-frequency spectral estimation. IEEE Trans Biomed Eng. 2009;56:2054–2063.PubMedCrossRef Chon KH, Dash S, Ju K. Estimation of respiratory rate from photoplethysmogram data using time-frequency spectral estimation. IEEE Trans Biomed Eng. 2009;56:2054–2063.PubMedCrossRef
3.
go back to reference Clifton D, Douglas JG, Addison PS, Watson JN. Measurement of respiratory rate from the photoplethysmogram in chest clinic patients. J Clin Monit Comput. 2007;21:55–61.PubMedCrossRef Clifton D, Douglas JG, Addison PS, Watson JN. Measurement of respiratory rate from the photoplethysmogram in chest clinic patients. J Clin Monit Comput. 2007;21:55–61.PubMedCrossRef
4.
go back to reference Dash S, Shelley KH, Silverman DG, Chon KH. Estimation of respiratory rate from ECG photoplethysmogram, and piezoelectric pulse transducer signals: a comparative study of time-frequency methods. IEEE Trans Biomed Eng. 2010;57:1099–1107.PubMedCrossRef Dash S, Shelley KH, Silverman DG, Chon KH. Estimation of respiratory rate from ECG photoplethysmogram, and piezoelectric pulse transducer signals: a comparative study of time-frequency methods. IEEE Trans Biomed Eng. 2010;57:1099–1107.PubMedCrossRef
5.
go back to reference Fleming S, Tarassenko L, Thompson M, Mant D. Non-invasive measurement of respiratory rate in children using the photoplethysmogram. Conf Proc IEEE Eng Med Biol Soc. 2008;2008:1886–1889.PubMed Fleming S, Tarassenko L, Thompson M, Mant D. Non-invasive measurement of respiratory rate in children using the photoplethysmogram. Conf Proc IEEE Eng Med Biol Soc. 2008;2008:1886–1889.PubMed
6.
go back to reference Fleming SG, Tarassenko L. A comparison of signal processing techniques for the extraction of breathing rate from the photoplethysmogram. Int J Biol Med Sci. 2007;2:232–236. Fleming SG, Tarassenko L. A comparison of signal processing techniques for the extraction of breathing rate from the photoplethysmogram. Int J Biol Med Sci. 2007;2:232–236.
7.
go back to reference Foo JY, Wilson SJ. Estimation of breathing interval from the photoplethysmographic signals in children. Physiol Meas. 2005;26:1049–1058.PubMedCrossRef Foo JY, Wilson SJ. Estimation of breathing interval from the photoplethysmographic signals in children. Physiol Meas. 2005;26:1049–1058.PubMedCrossRef
8.
go back to reference Johansson A. Neural network for photoplethysmographic respiratory rate monitoring. Med Biol Eng Comput. 2003;41:242–248.PubMedCrossRef Johansson A. Neural network for photoplethysmographic respiratory rate monitoring. Med Biol Eng Comput. 2003;41:242–248.PubMedCrossRef
9.
go back to reference Johansson A, Oberg PA, Sedin G. Monitoring of heart and respiratory rates in newborn infants using a new photoplethysmographic technique. J Clin Monit Comput. 1999;15:461–467.PubMedCrossRef Johansson A, Oberg PA, Sedin G. Monitoring of heart and respiratory rates in newborn infants using a new photoplethysmographic technique. J Clin Monit Comput. 1999;15:461–467.PubMedCrossRef
10.
go back to reference Johnston WS, Mendelson Y. Extracting breathing rate information from a wearable reflectance pulse oximeter sensor. Conf Proc IEEE Eng Med Biol Soc. 2004;7:5388–5391.PubMed Johnston WS, Mendelson Y. Extracting breathing rate information from a wearable reflectance pulse oximeter sensor. Conf Proc IEEE Eng Med Biol Soc. 2004;7:5388–5391.PubMed
11.
go back to reference Lee J, Chon KH. Respiratory rate extraction via an autoregressive model using the optimal parameter search criterion. Ann Biomed Eng. 2010;38:3218–3225.PubMedCrossRef Lee J, Chon KH. Respiratory rate extraction via an autoregressive model using the optimal parameter search criterion. Ann Biomed Eng. 2010;38:3218–3225.PubMedCrossRef
12.
go back to reference Leonard P, Beattie TF, Addison PS, Watson JN. Standard pulse oximeters can be used to monitor respiratory rate. Emerg Med J. 2003;20:524–525.PubMedCrossRef Leonard P, Beattie TF, Addison PS, Watson JN. Standard pulse oximeters can be used to monitor respiratory rate. Emerg Med J. 2003;20:524–525.PubMedCrossRef
13.
go back to reference Leonard P, Grubb NR, Addison PS, Clifton D, Watson JN. An algorithm for the detection of individual breaths from the pulse oximeter waveform. J Clin Monit Comput. 2004;18:309–312.PubMedCrossRef Leonard P, Grubb NR, Addison PS, Clifton D, Watson JN. An algorithm for the detection of individual breaths from the pulse oximeter waveform. J Clin Monit Comput. 2004;18:309–312.PubMedCrossRef
14.
go back to reference Leonard PA, Clifton D, Addison PS, Watson JN, Beattie T. An automated algorithm for determining respiratory rate by photoplethysmogram in children. Acta Paediatr. 2006;95:1124–1128.PubMedCrossRef Leonard PA, Clifton D, Addison PS, Watson JN, Beattie T. An automated algorithm for determining respiratory rate by photoplethysmogram in children. Acta Paediatr. 2006;95:1124–1128.PubMedCrossRef
15.
go back to reference Leonard PA, Douglas JG, Grubb NR, Clifton D, Addison PS, Watson JN. A fully automated algorithm for the determination of respiratory rate from the photoplethysmogram. J Clin Monit Comput. 2006;20:33–36.PubMedCrossRef Leonard PA, Douglas JG, Grubb NR, Clifton D, Addison PS, Watson JN. A fully automated algorithm for the determination of respiratory rate from the photoplethysmogram. J Clin Monit Comput. 2006;20:33–36.PubMedCrossRef
16.
go back to reference Lindberg LG, Ugnell H, Oberg PA. Monitoring of respiratory and heart rates using a fibre-optic sensor. Med Biol Eng Comput. 1992;30:533–537.PubMedCrossRef Lindberg LG, Ugnell H, Oberg PA. Monitoring of respiratory and heart rates using a fibre-optic sensor. Med Biol Eng Comput. 1992;30:533–537.PubMedCrossRef
17.
go back to reference Nilsson L, Johansson A, Kalman S. Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique. J Clin Monit Comput. 2000;16:309–315.PubMedCrossRef Nilsson L, Johansson A, Kalman S. Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique. J Clin Monit Comput. 2000;16:309–315.PubMedCrossRef
18.
go back to reference Nilsson L, Johansson A, Kalman S. Respiration can be monitored by photoplethysmography with high sensitivity and specificity regardless of anaesthesia and ventilatory mode. Acta Anaesthesiol Scand. 2005;49:1157–1162.PubMedCrossRef Nilsson L, Johansson A, Kalman S. Respiration can be monitored by photoplethysmography with high sensitivity and specificity regardless of anaesthesia and ventilatory mode. Acta Anaesthesiol Scand. 2005;49:1157–1162.PubMedCrossRef
19.
go back to reference Olsson E, Ugnell H, Oberg PA, Sedin G. Photoplethysmography for simultaneous recording of heart and respiratory rates in newborn infants. Acta Paediatr. 2000;89:853–861.PubMedCrossRef Olsson E, Ugnell H, Oberg PA, Sedin G. Photoplethysmography for simultaneous recording of heart and respiratory rates in newborn infants. Acta Paediatr. 2000;89:853–861.PubMedCrossRef
20.
go back to reference Shelley KH, Awad AA, Stout RG, Silverman DG. The use of joint time frequency analysis to quantify the effect of ventilation on the pulse oximeter waveform. J Clin Monit Comput. 2006;20:81–87.PubMedCrossRef Shelley KH, Awad AA, Stout RG, Silverman DG. The use of joint time frequency analysis to quantify the effect of ventilation on the pulse oximeter waveform. J Clin Monit Comput. 2006;20:81–87.PubMedCrossRef
21.
go back to reference Wertheim D, Olden C, Savage E, Seddon P. Extracting respiratory data from pulse oximeter plethysmogram traces in newborn infants. Arch Dis Child Fetal Neonatal Ed. 2009;94:F301–F303.PubMedCrossRef Wertheim D, Olden C, Savage E, Seddon P. Extracting respiratory data from pulse oximeter plethysmogram traces in newborn infants. Arch Dis Child Fetal Neonatal Ed. 2009;94:F301–F303.PubMedCrossRef
22.
go back to reference Zhou Y, Zheng Y, Wang C, Yuan J. Extraction of respiratory activity from photoplethysmographic signals based on an independent component analysis technique: preliminary report. Instrum Sci Technol. 2006;34:537–545.CrossRef Zhou Y, Zheng Y, Wang C, Yuan J. Extraction of respiratory activity from photoplethysmographic signals based on an independent component analysis technique: preliminary report. Instrum Sci Technol. 2006;34:537–545.CrossRef
23.
go back to reference Anderson JA, Vann WF. Respiratory monitoring during pediatric sedation: pulse oximetry and capnography. Pediatr Dent. 1998;10(2):94–101. Anderson JA, Vann WF. Respiratory monitoring during pediatric sedation: pulse oximetry and capnography. Pediatr Dent. 1998;10(2):94–101.
24.
go back to reference Branson RD, Mannheimer PD. Forehead oximetry in critically ill patients: the case for a new monitoring site. Respir Care Clin N Am. 2004;10:359–367.PubMedCrossRef Branson RD, Mannheimer PD. Forehead oximetry in critically ill patients: the case for a new monitoring site. Respir Care Clin N Am. 2004;10:359–367.PubMedCrossRef
Metadata
Title
Developing an algorithm for pulse oximetry derived respiratory rate (RRoxi): a healthy volunteer study
Authors
Paul S. Addison
James N. Watson
Michael L. Mestek
Roger S. Mecca
Publication date
01-02-2012
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 1/2012
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-011-9332-y

Other articles of this Issue 1/2012

Journal of Clinical Monitoring and Computing 1/2012 Go to the issue