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The Use of Joint Time Frequency Analysis to Quantify the Effect of Ventilation on the Pulse Oximeter Waveform

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Abstract

Objective. In the process of determining oxygen saturation, the pulse oximeter functions as a photoelectric plethysmograph. By analyzing how the frequency spectrum of the pulse oximeter waveform changes over time, new clinically relevant features can be extracted. Methods. Thirty patients undergoing general anesthesia for abdominal surgery had their pulse oximeter, airway pressure and CO2 waveforms collected (50 Hz). The pulse oximeter waveform was analyzed with a short-time Fourier transform using a moving 4096 point Hann window of 82 seconds duration. The frequency signal created by positive pressure ventilation was extracted using a peak detection algorithm in the frequency range of ventilation (0.08–0.4 Hz = 5–24 breaths/minute). The respiratory rate derived in this manner was compared to the respiratory rate as determined by CO2 detection. Results. In total, 52 hours of telemetry data were analyzed. The respiratory rate measured from the pulse oximeter waveform was found to have a 0.89 linear correlation when compared to CO2 detection and airway pressure change. the bias was 0.03 breath/min, SD was 0.557 breath/min and the upper and lower limits of agreement were 1.145 and −1.083 breath/min respectively. The presence of motion artifact proved to be the primary cause of failure of this technique. Conclusion. Joint time frequency analysis of the pulse oximeter waveform can be used to determine the respiratory rate of ventilated patients and to quantify the impact of ventilation on the waveform. In addition, when applied to the pulse oximeter waveform new clinically relevant features were observed.

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References

  1. Hertzman AB. The blood supply of various skin areas as estimated by the photoelectric plethysmograph. Am J Physiol 1938; 124: 328–340.

    Google Scholar 

  2. Dorlas JC, Nijboer JA. Photo-electric plethysmography as a monitoring device in anaesthesia. Application and interpretation. British Journal of Anaesthesia 1985; 57: 524–530.

    Article  PubMed  CAS  Google Scholar 

  3. Johansson A. Neural network for photoplethysmographic respiratory rate monitoring. Med Biol Eng Comput 2003; 41: 242–248.

    Article  PubMed  CAS  Google Scholar 

  4. Nakajima K, Tamura T, Miike H. Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique. Med Eng Phys 1996; 18: 365–372.

    Article  PubMed  CAS  Google Scholar 

  5. 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.

    Article  PubMed  CAS  Google Scholar 

  6. Johansson A, Oberg PA. Estimation of respiratory volumes from the photoplethysmographic signal. Part I: Experimental results. Med Biol Eng Comput 1999; 37: 42–47.

    Article  PubMed  CAS  Google Scholar 

  7. Partridge BL. Use of pulse oximetry as a noninvasive indicator of intravascular volume status. J Clin Monit 1987; 3: 263–268.

    PubMed  CAS  Google Scholar 

  8. Shamir M, Eidelman LA, Floman Y et al. Pulse oximetry plethysmographic waveform during changes in blood volume. Br J Anaesth 1999; 82: 178–181.

    PubMed  CAS  Google Scholar 

  9. Rusch TL, Sankar R, Scharf JE. Signal processing methods for pulse oximetry. Comput Biol Med 1996; 26: 143–159.

    Article  PubMed  CAS  Google Scholar 

  10. Stack BC, Jr., Futran ND, Shohet MJ, Scharf JE. Spectral analysis of photoplethysmograms from radial forearm free flaps. Laryngoscope 1998; 108: 1329–1333.

    Article  PubMed  Google Scholar 

  11. Leonard P, Grubb NR, Addison PS et al. An algorithm for the detection of individual breaths from the pulse oximeter waveform. J Clin Monit Comput 2004; 18: 309–312.

    Article  PubMed  Google Scholar 

  12. Bland JM, Altman DG. A note on the use of the intraclass correlation coefficient in the evaluation of agreement between two methods of measurement. Computers In Biology And Medicine 1990; 20: 337–340.

    Article  PubMed  CAS  Google Scholar 

  13. Shelley K, Tamai D, Jablonka D et al. The impact of venous pulsation on the forehead pulse oximeter waveform as a possible source of error in SpO2 calculation. Anesthesia & Analgesia 2004; 98: S12.

    Google Scholar 

  14. Shelley KH, Dickstein M, Shulman SM. The detection of peripheral venous pulsation using the pulse oximeter as a plethysmograph. J Clin Monit 1993; 9: 283–287.

    Article  PubMed  CAS  Google Scholar 

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Correspondence to Kirk H. Shelley MD, PhD.

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Shelley, K.H., Awad, A.A., Stout, R.G. et al. The Use of Joint Time Frequency Analysis to Quantify the Effect of Ventilation on the Pulse Oximeter Waveform. J Clin Monit Comput 20, 81–87 (2006). https://doi.org/10.1007/s10877-006-9010-7

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  • DOI: https://doi.org/10.1007/s10877-006-9010-7

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