Kirk H. Shelley

Photoplethysmography: Beyond the Calculation of Arterial Oxygen Saturation and Heart Rate

In this article, I examine the source of the photoplethysmograph (PPG), as well as methods of investigation, with an emphasize on amplitude, rhythm, and pulse analysis. The PPG waveform was first described in the 1930s. Although considered an interesting ancillary monitor, the “pulse waveform” never underwent intensive investigation. Its importance in clinical medicine was greatly increased with the introduction of the pulse oximeter into routine clinical care in the 1980s. Its waveform is now commonly displayed in the clinical setting. Active research efforts are beginning to demonstrate a utility beyond oxygen saturation and heart rate determination. Future trends are being heavily influenced by modern digital signal processing, which is allowing a re-examination of this ubiquitous waveform. Key to unlocking the potential of this waveform is an unfettered access to the raw signal, combined with standardization of its presentation, and methods of analysis. In the long run, we need to learn how to consistently quantify the characteristics of the PPG in such a way as to allow the results from research efforts be translated into clinically useful devices.

Different responses of ear and finger pulse oximeter wave form to cold pressor test.

The cold pressor test is often used to assess vasoconstrictive responses because it simulates the vasoconstrictive challenges commonly encountered in the clinical setting. With IRB approval, 12 healthy volunteers, aged 25–50 yr, underwent baseline plethysmographic monitoring on the finger and ear. The contralateral hand was immersed in ice water for 30 s to elicit a systemic vasoconstrictive response while the recordings were continued. The changes in plethysmographic amplitude for the first 30 s of ice water immersion (period of maximum response) of the finger and ear were compared. The data indicate a significant disparity between the finger and the ear signals in response to the cold stimulus. The average finger plethysmographic amplitude measurement decreased by 48% ± 19%. In contrast, no significant change was seen in the ear plethysmographic amplitude measurement, which decreased by 2% ± 10%. We conclude that the ear is relatively immune to the vasoconstrictive effects. These findings suggest that the comparison of the ear and finger pulse oximeter wave forms might be used as a real-time monitor of sympathetic tone and that the ear plethysmography may be a suitable monitor of the systemic circulation.

What is the best site for measuring the effect of ventilation on the pulse oximeter waveform

The cardiac pulse is the predominant feature of the pulse oximeter (plethysmographic) waveform. Less obvious is the effect of ventilation on the waveform. There have been efforts to measure the effect of ventilation on the waveform to determine respiratory rate, tidal volume, and blood volume. We measured the relative strength of the effect of ventilation on the reflective plethysmographic waveform at three different sites: the finger, ear, and forehead. The plethysmographic waveforms from 18 patients undergoing positive pressure ventilation during surgery and 10 patients spontaneously breathing during renal dialysis were collected. The respiratory signal was isolated from the waveform using spectral analysis. It was found that the respiratory signal in the pulse oximeter waveform was more than 10 times stronger in the region of the head when compared with the finger. This was true with both controlled positive pressure ventilation and spontaneous breathing. A significant correlation was demonstrated between the estimated blood loss from surgical procedures and the impact of ventilation on ear plethysmographic data (rs = 0.624, P = 0.006).

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

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.

The effect of venous pulsation on the forehead pulse oximeter wave form as a possible source of error in Spo2 calculation.

Reflective forehead pulse oximeter sensors have recently been introduced into clinical practice. They reportedly have the advantage of faster response times and immunity to the effects of vasoconstriction. Of concern are reports of signal instability and erroneously low Spo2 values with some of these new sensors. During a study of the plethysmographic wave forms from various sites (finger, ear, and forehead) it was noted that in some cases the forehead wave form became unexpectedly complex in configuration. The plethysmographic signals from 25 general anesthetic cases were obtained, which revealed the complex forehead wave form during 5 cases. We hypothesized that the complex wave form was attributable to an underlying venous signal. It was determined that the use of a pressure dressing over the sensor resulted in a return of a normal plethysmographic wave form. Further examination of the complex forehead wave form reveal a morphology consistent with a central venous trace with atrial, cuspidal, and venous waves. It is speculated that the presence of the venous signal is the source of the problems reported with the forehead sensors. It is believed that the venous wave form is a result of the method of attachment rather than the use of reflective plethysmographic sensors.

Estimation of Respiratory Rate From ECG, Photoplethysmogram, and Piezoelectric Pulse Transducer Signals: A Comparative Study of Time–Frequency Methods

We compare the performance of two different time-frequency-based breathing rate (BR) detection algorithms when used on three different physiological signals: the ECG, the photoplethysmogram (PPG), and the piezoelectric pulse transducer (PZO) signal. Studies carried out over the past have shown the existence of amplitude and/or FMs due to respiration in physiological signals, such as those mentioned. In a recent study, we analyzed the PPG signal and detected the FM and amplitude modulation effect that controlled breathing had on it, and inferred the rate of respiration using the time-frequency spectrum (TFS) (via a wavelet (WT) or complex demodulation (CDM) approach). We showed that such TFS BR detection methods were very accurate and consistently outperformed the exclusively time-domain autoregressive modeling (AR) method, especially in the real-time (data length of 1 min) case. We now explore the possibility of using these methods on the ECG and the finger PZO signal, of which only the former has been previously used with some success to derive BR. Testing performed on 15 healthy human subjects for a range of BR and two body positions showed that though the PPG signal gave the most consistently high performance, the ECG and PZO also proved to be reasonably accurate over longer time segments. Furthermore, the CDM approach was on average either better than or comparable to the WT method in terms of both accuracy and repeatability of the detection.

How Does the Plethysmogram Derived from the Pulse Oximeter Relate to Arterial Blood Pressure in Coronary Artery Bypass Graft Patients

Twenty patients scheduled for coronary artery bypass grafting had their ear and finger oximeter and radial artery blood pressure (Bpmeas) waveforms collected. The ear and finger pulse oximeter waveforms were analyzed to extract beat-to-beat amplitude and area and width measurements. The Bpmeas waveforms were analyzed to measured systolic blood pressure (BP), mean BP, and pulse pressure. The correlation coefficient was determined between the derived waveforms from the pulse oximeter and Bpmeas for the first 10 patients. The ear pulse oximeter width (WidthEar) had the best correlation (r = 0.8). Linear regression was done between WidthEar and Bpmeas based on slope (b) and intercept (a) values, BP was calculated (Bpcalc) in the next 10 patients as:MATHwhere i = systolic BP, mean BP, and pulse pressure. The initial bias was too large to be clinically useful. To improve clinical applicability a period of calibration was introduced in which the first 50 readings of WidthEar and Bpmeas for each patient were used to calculate the intercept. After calibration the systolic BP, mean BP and pulse pressure bias values were −2.6, −1.88 and −1.28 mm Hg, and the precision values were 15.9 10.09, and 9.94 mm Hg, respectively. The present attempt to develop a clinically useful method of noninvasive BP measuring was partly successful with the requirement of a calibration period.

Virtual environments in healthcare: immersion, disruption, and flow.

Old forms of education are slowly crumbling under the weight of rapidly advancing computer and communication technologies along with the demands of learners who have grown up digital. These advances necessitate new thinking about the ways we educate and assess our healthcare workforce. Choosing anesthesiology (or any other healthcare profession) constitutes a commitment to life-long learning. Our careers span decades, and therefore, we need to constantly update our knowledge and skills. Yet, the traditional model of medical education has not changed in more than 100 years. The majority of our preclinical, and continuing education comes in the form of passive teacher-centric lectures. To paraphrase an example used by Sir Ken Robinson in his book, The Element, if we had a time machine and were able to bring a student forward in time from the 18th century, our educational system would be one of the few parts of society they would recognize.

Analysis of the ear pulse oximeter waveform

Objective: For years researchers have been attempting to understand the relationship between central hemodynamics and the resulting peripheral waveforms. This study is designed to further understanding of the relationship between ear pulse oximeter waveforms, finger pulse oximeter waveforms and cardiac output (CO). It is hoped that with appropriate analysis of the peripheral waveforms, clues can be gained to help to optimize cardiac performance. Methods.Part 1: Studying the effect of cold immersion test on plethysmographic waveforms. Part 2: Studying the correlation between ear and finger plethysmographic waveforms and (CO) during CABG surgery. The ear and finger plethysmographic waveforms were analyzed to determine amplitude, width, area, upstroke and downslope. The CO was measured using continuous PA catheter. Using multi-linear regression, ear plethysmographic waveforms, together with heart rate (HR), were used to determine the CO Agreement between the two methods of CO determination was assessed. Results.Part 1: On contralateral hand immersion, all finger plethysmographic waveforms were reduced, there was no significant change seen in ear plethysmographic waveforms, except an increase in ear plethysmographic width. Part 2: Phase1: Significant correlation detected between the ear plethysmographic width and other ear and finger plethysmographic waveforms. Phase 2: The ear plethysmographic width had a significant correlation with the HR and CO. The correlation of the other ear plethysmographic waveforms with CO and HR are summarized (Table 5). Multi-linear regression analysis was done and the best fit equation was found to be: CO = 8.084 − 14.248 × Ear width + 0.03 ×HR+ 92.322 × Ear down slope+0.027 × Ear Area Using Bland & Altman, the bias was (0.05 L) but the precision (2.46) is large to be clinically accepted. Conclusion. The ear is relatively immune to vasoconstrictive challenges which make ear plethysmographic waveforms a suitable monitor for central hemodynamic changes. The ear plethysmographic width has a good correlation with CO.

A Novel Approach Using Time–Frequency Analysis of Pulse-Oximeter Data to Detect Progressive Hypovolemia in Spontaneously Breathing Healthy Subjects

Accurate and early detection of blood volume loss would greatly improve intraoperative and trauma care. This study has attempted to determine early diagnostic and quantitative markers for blood volume loss by analyzing photoplethysmogram (PPG) data from ear, finger, and forehead sites with our high-resolution time-frequency spectral (TFS) technique in spontaneously breathing healthy subjects (n=11) subjected to lower body negative pressure (LBNP). The instantaneous amplitude modulations (AM) present in heart rate (AMHR) and breathing rate (AMBR) band frequencies of PPG signals were calculated from the high-resolution TFS. Results suggested that the changes (P <; 0.05) in AMBR and especially in AMHR values can be used to detect the blood volume loss at an early stage of 20% LBNP tolerance when compared to the baseline values. The mean percent decrease in AMHR values at 100% LBNP tolerance was 78.3%, 72.5%, and 33.9% for ear, finger, and forehead PPG signals, respectively. The mean percent increase in AMBR values at 100% LBNP tolerance was 99.4% and 19.6% for ear and finger sites, respectively; AMBR values were not attainable for forehead PPG signal. Even without baseline AMHR values, our results suggest that hypovolemia detection is possible with specificity and sensitivity greater than 90% for the ear and forehead locations when LBNP tolerance is 100%. Therefore, the TFS analysis of noninvasive PPG waveforms is promising for early diagnosis and quantification of hypovolemia at levels not identified by vital signs in spontaneously breathing subjects.