In this issue of Anesthesia & Analgesia, we have 2 closely related papers that reach seemingly incompatible conclusions regarding the interpretation of the pulse oximeter waveform.1,2 Addison1 presents an extensive review of advanced signal processing used for the analysis of the modulation of the pulse oximeter waveform (also known as the photoplethysmogram, PPG, or “pleth”) and how it can guide fluid replacement in the patient during mechanical ventilation. In a technical report, Perel2 shows that the same waveform can be used to detect respiratory obstruction and asthma in spontaneously breathing patients. Are both correct? Can the same waveform monitor oxygen saturation, guide fluid-replacement therapy, and spot airway obstruction?
These 2 studies demonstrate that the pulse oximeter waveform provides much information beyond heart rate and oxygen saturation.3 However, it will take solid biomedical engineering, advanced signal processing, and clinical insight to bring this information to the bedside.
The pulse oximeter waveform is not a new discovery. It was first described by Hertzman and Spielman in 1937,4 and it was Hertzman who named it the photoelectric plethysmograph based upon his belief, and early observations, that its creation was linked to blood volume changes. He chose the term “plethysmos,” which is derived from the Greek word for fullness. The choice came from his belief that he was measuring the fullness of the tissue when he measured the amount of light absorption. Subsequent research, which revealed a close correlation between the photoplethysmogram and the more traditional strain gauge plethysmograph, has demonstrated he was not far off on his assumptions.5 Today, it is one of the most commonly displayed clinical waveforms.
The technology behind the photoplethysmogram is very simple. The waveform is an amplified and highly filtered measurement of light absorption by the local tissue over time. It is optimized by medical device manufacturers to accentuate its pulsatile components and to make the waveform appear with the same features as the arterial pressure waveform. Physiologically, it is the result of a complex and poorly understood interaction among the cardiovascular, respiratory, and autonomic systems.
We do not know for certain the level of the vasculature that creates the signal. The general consensus is that the cardiac component of the waveform comes from the site of maximum pulsation within the arteriolar vessels, where pulsatile energy is converted to smooth flow just before the level of the capillaries.6 There is growing evidence that the respiratory-induced modulation of the waveform is caused by the movement of venous blood.7,8
The typical photoplethysmogram, as displayed on a clinical monitor, is a highly filtered signal. The photoplethysmogram has undergone filtering via band-pass filters (autocentering and smoothing) as well as variable amplification (autogain) before the clinician ever sees it. It is a misconception to believe that this waveform can be analyzed using simple tools such as those used for the analysis of the arterial pressure waveform.9
Anesthesiologists studying the pulse oximeter waveform should be vigilant when using commercially available clinical monitors in ways not envisioned by their manufacturers. In his 2006 editorial, Feldman10 pointed out the inherent limitations of using clinical monitors as research instruments. His primary concern was the potential for misleading research conclusions. This is analogous to the common clinical practice of “off-label” use of pharmaceutical agents. Just as pharmacists are involved in the research focusing on the development of pharmaceutical agents, it is critical to get biomedical engineers involved in extending use of this waveform. Extracting the richness of information contained in the photoplethysmogram will require sophisticated signal-processing skills combined with innovative physiologic approaches (e.g., modeling the interactions between the venous and arterial systems).
The development of clinical monitors for critical care and perioperative settings should follow a logical path, starting with the understanding of the physiology (the mental model one has of the underlying physiology), the technology (what is recorded and how should it be analyzed), as well as how the information should be presented to the clinician. The engineers also must consider the therapeutic options that will be guided by the information provided by the monitor. There is no point in providing an accurate monitor that does not guide clinical decisions. What would you do with a highly accurate, real-time monitor of serum creatinine? Probably nothing. Although large, randomized studies of pulse oximetry did not show any improvement in patient outcome,11 studies have documented benefits in fluid management guided by the photoplethysmogram.12
We are just starting to tap the information in the photoplethysmogram. The next few decades will see further innovations related to this waveform, extending the research trajectory of the past 10 years.3,13 These advances will be the product of close collaboration among academic anesthesiologists, engineers, physiologists, and industry leaders. The beneficiaries will be our patients.
Name: Kirk Shelley, MD, PhD.
Contribution: This author helped write the manuscript.
Attestation: Kirk Shelley approved the final manuscript.
Conflicts of Interest: Patent applications have been submitted for some of the technology presented in this editorial. Yale University is the assignee.
Name: Maxime Cannesson, MD, PhD.
Contribution: This author helped write the manuscript.
Attestation: Maxime Cannesson approved the final manuscript.
Conflicts of Interest: Maxime Cannesson consulted for Edwards Lifesciences, received research funding from Edwards Lifesciences, consulted for Masimo, received research funding from Masimo, has equity interest in Sironis, has equity interest in Gauss, and consulted for Covidien.
Dr. Maxime Cannesson is the Section Editor for Technology, Computing, and Simulation for Anesthesia & Analgesia. This manuscript was handled by Dr. Steven L. Shafer, Editor-in-Chief, and Dr. Cannesson was not involved in any way with the editorial process or decision.
1. Addison PS. A review of signal processing used in the implementation of the pulse oximetry photoplethysmographic fluid responsiveness parameter. Anesth Analg. 2014;119:1293–306
2. Perel A. Excessive variations in the plethysmographic waveform during spontaneous ventilation: an important sign of upper airway obstruction. Anesth Analg. 2014;;119:1288–92
3. Shelley KH. Photoplethysmography: beyond the calculation of arterial oxygen saturation and heart rate. Anesth Analg. 2007;105:S31–6
4. Hertzman AB, Spielman C. Observations on the finger volume pulse recorded photoelectrically. Am J Physiol. 1937;119:334–5
5. de Trafford J, Lafferty K. What does photoplethysmography measure? Med Biol Eng Comput. 1984;22:479–80
6. Spigulis J. Optical noninvasive monitoring of skin blood pulsations. Appl Opt. 2005;44:1850–7
7. Phillips JP, Belhaj A, Shafqat K, Langford RM, Shelley KH, Kyriacou PA. Modulation of finger photoplethysmographic traces during forced respiration: venous blood in motion? Conf Proc IEEE Eng Med Biol Soc. 2012;2012:3644–7
8. Walton ZD, Kyriacou PA, Silverman DG, Shelley KH. Measuring venous oxygenation using the photoplethysmograph waveform. J Clin Monit Comput. 2010;24:295–303
9. Cannesson M, Manach YL. Noninvasive hemodynamic monitoring: no high heels on the farm; no clogs to the opera. Anesthesiology. 2012;117:937–9
10. Feldman JM. Can clinical monitors be used as scientific instruments? Anesth Analg. 2006;103:1071–2
11. Shah A, Shelley KH. Is pulse oximetry an essential tool or just another distraction? The role of the pulse oximeter in modern anesthesia care. J Clin Monit Comput. 2013;27:235–42
12. Forget P, Lois F, de Kock M. Goal-directed fluid management based on the pulse oximeter-derived pleth variability index reduces lactate levels and improves fluid management. Anesth Analg. 2010;111:910–4
13. Cannesson M, Talke P. Recent advances in pulse oximetry. F1000 Med Rep. 2009;1:66