Research Papers: Sensing

Relations between ac-dc components and optical path length in photoplethysmography

[+] Author Affiliations
Chungkeun Lee, Hang Sik Shin, Myoungho Lee

Yonsei University, School of Electrical and Electronic Engineering, Sinchon-dong, Seodaemoon-gu, Seoul, 120-749 Republic of Korea

J. Biomed. Opt. 16(7), 077012 (July 22, 2011). doi:10.1117/1.3600769
History: Received March 05, 2011; Revised May 10, 2011; Accepted May 26, 2011; Published July 22, 2011; Online July 22, 2011
Text Size: A A A

Open Access Open Access

* Adderess all correspondence to: Myoungho Lee, Yonsei University, Department of Electrical and Electronic Engineering, 212C, Yonsei Engineering Research Center, 134 Sinchon-dong, Seodaemoon-gu, Seoul, 120-749 Republic of Korea; Tel: +82-2-2123-4947; Fax: +82-2-312-2770; E-mail: mhlee@yonsei.ac.kr.

Photoplethysmography is used in various areas such as vital sign measurement, vascular characteristics analysis, and autonomic nervous system assessment. Photoplethysmographic signals are composed of ac and dc, but it is difficult to find research about the interaction of photoplethysmographic components. This study suggested a model equation combining two Lambert–Beer equations at the onset and peak points of photoplethysmography to evaluate ac characteristics, and verified the model equation through simulation and experiment. In the suggested equation, ac was dependent on dc and optical path length. In the simulation, dc was inversely proportionate to ac sensitivity (slope), and ac and optical path length were proportionate. When dc increased from 10% to 90%, stabilized ac decreased from 1 to 0.89 ± 0.21, and when optical path length increased from 10% to 90%, stabilized ac increased from 1 to 1.53 ± 0.40.

Figures in this Article

Photoplethysmography (PPG) is composed of a pulsatile component (ac) and nonpulsatile component (dc). ac is synchronized with the heart and related to arterial pulsation, while dc is related to light absorption in the tissue, vein, and diastolic arterial blood volume. dc has many physiological meanings and correlates with the ac waveform.18 According to the Lambert–Beer (or Beer–Lambert) law that explains mechanisms of PPG, PPG ac is generated by the optical path length (Δd) that changes with the increase of volume in blood vessels as they pulsate.9 Therefore, it can be said that PPG ac is in a consistent relationship generated by variations in dc and Δd.

In previous studies of ac, dc, and Δd, there were correlations between continuous ac and spontaneous variations of dc,10 but there has been no research on ac variation according to dc intensity. There have also been comparative studies of preop and postop blocking of sympathetic nerve systems or specific patients such as diabetics.3,1113 However, these studies only reported on experimental results and did not suggest a mathematical model that can explain the relationship between components, so they offer limited explanations of physiological results. Therefore, this study suggested an equation for the relationship between ac, dc, and components using the existing Lambert–Beer law to analyze the characteristics of PPG as a noninvasive vascular assessment tool. Results of the suggested equation were assessed through simple simulation and experiment.

Optical Model

Based on the Lambert–Beer law, the photodetector detects photons not absorbed into the blood. The waveform of general photoplethysmography used in many studies can be gained by inversing or subtracting the amount of light not absorbed at a constant (k).3 This is shown in Fig. 1, and the onset and peak of the photoplethysmography can be presented as Eqs. 12.14Display Formula

1IH=IOeb dc d dc eb Hb + HbO 2dmin=αβdmin=kI onset ,
Display Formula
2IL=IOeb dc d dc eb Hb + HbO 2dmax=αβdmax=kI peak .
Here, IL is the small value of reflected amount of light and the peak point of PPG. IH is the large value of the reflected amount of light and the onset point of photoplethysmography. bdc is a function of the absorption and the attenuation constants, and equation is bdc = εdc(λ)cdc. εdc(λ), cdc, ddc each represent extinction coefficient, concentration of absorbing substance, and optical path length, respectively, that form extra-vascular photoplethysmography dc. λ stands for wavelength, and Hb and HbO2 represent hemoglobin and oxyhemoglobin, respectively. dmin is the basal diameter of arterial vessel before pulsation and dmax is the maximum variation of arterial diameter during pulsation. The square of arterial diameter is proportionate to the amount of blood. If each ε and c are constant during a heartbeat, α=IOeb dc d dc and β=eb Hb + HbO 2 can be substituted into Eqs. 12.

Graphic Jump LocationF1 :

Typical photoplethysmographic signal. (a) A raw signal measured from a photodetector. (b) Final signal, constant k-reflected light intensity.

PPG ac(Iac) is ILIH, the subtraction of onset from peak, and is shown in Eqs 35, and (6) using variations in optic path length Δd( = dmaxdmin). Display Formula

3I ac =ILIH,

Display Formula

4=αβdminαβdmax,
Display Formula
5=αβdminαβdmin+Δd,
Display Formula
6I ac =α(βdminβdmin+Δd)=αβdmin(1βΔd)=(kI onset )·(1βΔd).
According to Eq. 6, Iac (a component of ac) is inversely proportionate to Ionset, proportionate to arterial diameter variation Δd, and has nonlinear characteristics. Ionset is a dc component of photoplethysmography and stands for nonpulsatile components and basal blood volume before pulsation. Δd is affected by arterial stiffness and generates Iac. When Eq. 6 is transformed like Eq. 7, Δd can be estimated. Display Formula
7Δd= abs ln1I ac kI onset .
Numerical simulation was conducted to analyze the characteristics of ac components according to Ionset and Δd. Constant k was set up as 10 because signals voltage range of acquisition in the most commercial product for measuring biomedical data is ±10 V.1516Ionset increased in units of 0.001 from 0 to 10. Δd is converted approximately 0.04 mm when photoplethysmography is generated,9 so it was increased from 0 to 1 mm in units of 1 μm. The size of PPG ac calculated from each combination of Ionset and Δd was divided by the largest value, stabilized, and then analyzed.

Subject

A total of 20 subjects (15 male, 5 female, age 23.1±3.4, BMI 22.4±2.0 kg/m2) who consented to the experimental objective and progress participated. Subjects did not have cardiovascular or respiratory disease and were prohibited from drinking alcohol, smoking cigarettes, and drinking coffee one day before the experiment.

Experiment

In this experiment, respiration, ECG, and PPG were measured for 5 min in the supine position, as can be seen in Fig. 2. All signals were measured using ECG100C, PPG100C, and SKT100C (BIOPAC System, Inc., Goleta, California), with a 1 kHz sampling rate. PPG was measured on the left index finger, and using a TSD100 reflection-type sensor, it was set to 20× amplification in the 0.05 to 10 Hz bandwidth. ECG was used to identify the beat of PPG using a Lead II and amplified 2000× in the 0.5 to 35 Hz bandwidth.

Respiration was used to observe the rapid change in ac and dc due to deep inspiration, and it was measured via the Nasal method using a TSD202 sensor.17 The experiment setting was maintained at room temperature.

Signal Processing and Analysis

The QRS of ECG was detected using the Pan-Tompkin algorithm.18 Constant 10 was added to PPG to make a relative baseline with no negative voltage, and the onset and peak point of PPG was detected using the adaptive mood detection algorithm.19 Noise was removed from respiration through an 11-point moving average filter. PPG beats with ECG beats, and no rapid changes in ac and dc due to deep inspiration were selected. Δd was derived from Eq. 5. dc and Δd were transformed from the 10th to the 90th percentile distribution for the characteristic analysis of ac, and the ac value was stabilized by dividing it with the mean ac value of dc 10th percentile. All signal processing was conducted using MATLAB (Mathworks, Natick, Massachusetts).

Statistical Analysis

All data were expressed as mean ± standard deviation. SPSS (SPSS-IBM Inc, Chicago, Illinois) was used for statistical analysis. The ac characteristic curve was estimated using cubic regression (3rd polynomial regression). A p-value of <0.05 was considered statistically significant.

Figure 3 is a numerical simulation of stabilized ac characteristics with constant parameters (dc, Δd) in Eq. 6. Figure 3 shows characteristics of ac components according to Δd when dc is constant. As the dc value increased, the ac slope (sensitivity) toward increase in Δd decreased. Figure 3 shows the response of ac component characteristics according to dc when Δd is constant. When Δd increased, the slope of ac raised in dc increased.

Graphic Jump LocationF3 :

Computed ac characteristics of proposed model equation. (a) ac-Δd characteristics with fixed dc and (b) ac-dc characteristics with fixed Δd.

Figure 4 shows the ac characteristics according to dc and Δd percentile distribution obtained from actual experiment. In Fig. 4, when Δd was increased from the 10th percentile distribution to the 90th percentile distribution, stabilized ac increased from 1 ± 0 to 1.53 ± 0.40. The curve fitting equation was y = 0.000001368x3 − 0.00022x2 + 0.01621x + 0.8627(adj. R2 = 0.9997, p < 0.0001). In Fig. 4, when dc was increased from the 10th percentile distribution to the 90th percentile distribution, stabilized ac decreased from 1 ± 0 to 0.89 ± 0.21. The curve fitting equation was y = −0.3898x3 + 0.3028x2 − 0.07596x + 1.009(adj. R2 = 0.9273, p < 0.0001).

Graphic Jump LocationF4 :

ac characteristics by increasing Δd and dc percentile distribution. (a) ac-Δd and (b) ac-dc.

This study investigated ac characteristics according to the nonpulsatile component (dc) and optical path length (Δd) to analyze characteristics of PPG components.

In the equation suggested to analyze ac characteristics, ac was dependent on dc and Δd. dc was inversely proportionate to ac, and Δd was proportionate to ac. Nonpulsatile components are related to tissue, vein, and diastolic arterial blood volume. Light absorption of other tissue, such as skin pigment, dye, and bone, were disregarded because it does not change according to blood flow, which means weak changes in continuous PPG signals.

From nonpulsatile components, venous capacity during respiratory change is connected to respiratory-induced fluctuation in the dc component, which is highly correlated to central and periphery venous pressure.1,6 Venous capacity corresponds with venous return that affects blood capacity of the heart in each contraction. If venous tone in consistent in the venous return curve, venous return decreases with the increase in central venous pressure and decreases stroke volume. At this point, the autonomous nervous system increases heartbeat and arterial pressure to maintain homeostasis (maintain cardiac output).2,7 PPG ac is proportionate to stroke volume, so when PPG dc is increased due to increase in central venous pressure, this increases arterial pressure, leading to a decrease in PPG ac components.2,7

The second nonpulsatile component in PPG is the arterial nonpulsatile component, which signifies the baseline blood capacity of the artery in contraction, and this baseline blood capacity is proportionate to diameter.20 Arterial nonpulsatile components increase as arterial capacity or diameter increases. According to the stress-strain curve of the artery, the diameter is nonlinearly proportionate to blood pressure, and high blood pressure has high stiffness.20 Therefore, an increase in arterial nonpulsatile components increases vascular stiffness, which then decreases ac. From the two cases above, ac decreases according to an increase in PPG dc shown in the proposed equation, and the experiment is in accord with existing physiological research.

ac characteristics according to dc and Δd generated transition characteristics starting from each median point. In experimental characteristics against dc, attenuation appeared differently at the 50th percentile, and as transition happened in Δd, ac increased. According to existing research,8,21 on mechanical properties of normal subjects’ peripheral blood vessels, as blood pressure increases, compliance and distensibility of the artery exponentially decreased with an inflection point, and diameter exponentially increases. Therefore, it can be concluded that the transition characteristics of ac shown in attenuation and an increase of experimental results follow the mechanical properties of blood pressure-diameter.

In conclusion, an equation to explain ac characteristics was suggested, and its dependence on dc and Δd was verified through a simple simulation and experiment. Our results may be utilized as a basic analysis tool for noninvasive vascular assessment.

Nilsson  L., , Johansson  A., , and Kalman  S., “ Respiratory variations in the reflection mode photoplethysmographic signal. Relationships to peripheral venous pressure. ,” Med. Biol. Eng. Comput.. 41, (3 ), 249–254  ((2003)).
Nilsson  L., , Johansson  A., , and Kalman  S., “ Macrocirculation is not the sole determinant of respiratory induced variations in the reflection mode photoplethysmographic signal. ,” Physiol. Meas.. 24, (4) 925–937  ((2003)).
Nitzan  M., , Babchenko  A., , Khanokh  B., , and Landau  D., “ The variability of the photoplethysmographic signal—a potential method for the evaluation of the autonomic nervous system. ,” Physiol. Meas.. 19, (1 ), 93–102  ((1998)).
Nitzan  M., , Faib  I., , and Friedman  H., “ Respiration-induced changes in tissue blood volume distal to occluded artery, measured by photoplethysmography. ,”J. Biomed. Opt.. 11, (4 ), 040506  ((2006)).
Reisner  A., , Shaltis  P., , McCombie  D., , and Asada  H., “ Utility of the photoplethysmogram in circulatory monitoring. ,” Anesthesiology. 108, (5 ), 950–958  ((2008)).
Shelley  K. H., , Silverman  D. G., , Shelley  A. J., , and Stout  R. G., “ Method of assessing blood volume using photoelectric plethysmography. ,” U.S. Patent No. 2010/0016739 ((2010)).
Shelley  K. H., , Silverman  D. G., , and Shelley  A. J., “ Volume status monitor: Peripheral venous pressure, hypervolemia and coherence analysis. ,” WIPO Patent No. 2010/045556 ((2010)).
Tardy  Y., , Meister  J. J., , Perret  F., , Brunner  H. R., , and Arditi  M., “ Non-invasive estimate of the mechanical properties of peripheral arteries from ultrasonic and photoplethysmographic measurements. ,” Clin. Phys. Physiol. Meas.. 12, (1 ), 39–54  ((1991)).
Aldrich  T. K., , Moosikasuwan  M., , Shah  S. D., , and Deshpande  K. S., “ Length-normalized pulse photoplethysmography: a noninvasive method to measure blood hemoglobin. ,” Ann. Biomed. Eng.. 30, (10 ), 1291–1298  ((2002)).
Nitzan  M., , Babchenko  A., , and Khanokh  B., “ Very low frequency variability in arterial blood pressure and blood volume pulse. ,” Med. Biol. Eng. Comput.. 37, (1 ), 54–58  ((1999)).
Zheng  J., , Hu  S., , Xin  S., , and Crabtree  V., “ Effect of postural changes on lower limb blood volume, detected with non-invasive photoplethysmography. ,” J. Med. Eng. Technol.. 32, (5 ), 358–364  ((2008)).
Teng  X. F., and Zhang  Y. T., “ The effect of contacting force on photoplethysmographic signals. ,” Physiol. Meas.. 25, (5 ), 1323–1335  ((2004)).
Tanaka  G., and Sawada  Y., “ Examination of normalized pulse volume-blood volume relationship: toward a more valid estimation of the finger sympathetic tone. ,” Int. J. Psychophysiol.. 48, (3 ), 293–306  ((2003)).
Webster  J.,  Design of Pulse Oximeters. ,  Taylor & Francis ,  London  ((1997)).
National Instruments, http://www.ni.com.
Allen  J., , Frame  J. R., , and Murray  A., “ Microvascular blood flow and skin temperature changes in the fingers following a deep nspiratory gasp. ,” Physiol. Meas.. 23, (2 ), 365–373  ((2002)).
Pan  J., and Tompkins  W. J., “A real-time QRS detection algorithm,” IEEE Trans. Biomed. Eng.. 32, (3 ), 230–236  ((1985)).
Shin  H., , Lee  C., , and Lee  M., “ Adaptive threshold method for the peak detection of photoplethysmographic waveform. ,” Comput. Biol. Med.. 39, (12 ), 1145–1152  ((2009)).
Nichols  W. W., , O’Rourke  M. F., , and McDonald  D. A.,  McDonald's Blood Flow in Arteries: Theoretic, Experimental, and Cinical Principles. ,  Oxford University Press ,  London  ((2005)).
Hayoz  D., , Rutschmann  B., , Perret  F., , Niederberger  M., , Tardy  Y., , Mooser  V., , Nussberger  J., , Waeber  B., , and Brunner  H. R., “ Conduit artery compliance and distensibility are not necessarily reduced in hypertension. ,” Hypertension. 20, (1 ), 1–6  ((1992)).
© 2011 Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation

Chungkeun Lee ; Hang Sik Shin and Myoungho Lee
"Relations between ac-dc components and optical path length in photoplethysmography", J. Biomed. Opt. 16(7), 077012 (July 22, 2011). ; http://dx.doi.org/10.1117/1.3600769


Figures

Graphic Jump LocationF3 :

Computed ac characteristics of proposed model equation. (a) ac-Δd characteristics with fixed dc and (b) ac-dc characteristics with fixed Δd.

Graphic Jump LocationF4 :

ac characteristics by increasing Δd and dc percentile distribution. (a) ac-Δd and (b) ac-dc.

Graphic Jump LocationF1 :

Typical photoplethysmographic signal. (a) A raw signal measured from a photodetector. (b) Final signal, constant k-reflected light intensity.

Tables

References

Nilsson  L., , Johansson  A., , and Kalman  S., “ Respiratory variations in the reflection mode photoplethysmographic signal. Relationships to peripheral venous pressure. ,” Med. Biol. Eng. Comput.. 41, (3 ), 249–254  ((2003)).
Nilsson  L., , Johansson  A., , and Kalman  S., “ Macrocirculation is not the sole determinant of respiratory induced variations in the reflection mode photoplethysmographic signal. ,” Physiol. Meas.. 24, (4) 925–937  ((2003)).
Nitzan  M., , Babchenko  A., , Khanokh  B., , and Landau  D., “ The variability of the photoplethysmographic signal—a potential method for the evaluation of the autonomic nervous system. ,” Physiol. Meas.. 19, (1 ), 93–102  ((1998)).
Nitzan  M., , Faib  I., , and Friedman  H., “ Respiration-induced changes in tissue blood volume distal to occluded artery, measured by photoplethysmography. ,”J. Biomed. Opt.. 11, (4 ), 040506  ((2006)).
Reisner  A., , Shaltis  P., , McCombie  D., , and Asada  H., “ Utility of the photoplethysmogram in circulatory monitoring. ,” Anesthesiology. 108, (5 ), 950–958  ((2008)).
Shelley  K. H., , Silverman  D. G., , Shelley  A. J., , and Stout  R. G., “ Method of assessing blood volume using photoelectric plethysmography. ,” U.S. Patent No. 2010/0016739 ((2010)).
Shelley  K. H., , Silverman  D. G., , and Shelley  A. J., “ Volume status monitor: Peripheral venous pressure, hypervolemia and coherence analysis. ,” WIPO Patent No. 2010/045556 ((2010)).
Tardy  Y., , Meister  J. J., , Perret  F., , Brunner  H. R., , and Arditi  M., “ Non-invasive estimate of the mechanical properties of peripheral arteries from ultrasonic and photoplethysmographic measurements. ,” Clin. Phys. Physiol. Meas.. 12, (1 ), 39–54  ((1991)).
Aldrich  T. K., , Moosikasuwan  M., , Shah  S. D., , and Deshpande  K. S., “ Length-normalized pulse photoplethysmography: a noninvasive method to measure blood hemoglobin. ,” Ann. Biomed. Eng.. 30, (10 ), 1291–1298  ((2002)).
Nitzan  M., , Babchenko  A., , and Khanokh  B., “ Very low frequency variability in arterial blood pressure and blood volume pulse. ,” Med. Biol. Eng. Comput.. 37, (1 ), 54–58  ((1999)).
Zheng  J., , Hu  S., , Xin  S., , and Crabtree  V., “ Effect of postural changes on lower limb blood volume, detected with non-invasive photoplethysmography. ,” J. Med. Eng. Technol.. 32, (5 ), 358–364  ((2008)).
Teng  X. F., and Zhang  Y. T., “ The effect of contacting force on photoplethysmographic signals. ,” Physiol. Meas.. 25, (5 ), 1323–1335  ((2004)).
Tanaka  G., and Sawada  Y., “ Examination of normalized pulse volume-blood volume relationship: toward a more valid estimation of the finger sympathetic tone. ,” Int. J. Psychophysiol.. 48, (3 ), 293–306  ((2003)).
Webster  J.,  Design of Pulse Oximeters. ,  Taylor & Francis ,  London  ((1997)).
National Instruments, http://www.ni.com.
Allen  J., , Frame  J. R., , and Murray  A., “ Microvascular blood flow and skin temperature changes in the fingers following a deep nspiratory gasp. ,” Physiol. Meas.. 23, (2 ), 365–373  ((2002)).
Pan  J., and Tompkins  W. J., “A real-time QRS detection algorithm,” IEEE Trans. Biomed. Eng.. 32, (3 ), 230–236  ((1985)).
Shin  H., , Lee  C., , and Lee  M., “ Adaptive threshold method for the peak detection of photoplethysmographic waveform. ,” Comput. Biol. Med.. 39, (12 ), 1145–1152  ((2009)).
Nichols  W. W., , O’Rourke  M. F., , and McDonald  D. A.,  McDonald's Blood Flow in Arteries: Theoretic, Experimental, and Cinical Principles. ,  Oxford University Press ,  London  ((2005)).
Hayoz  D., , Rutschmann  B., , Perret  F., , Niederberger  M., , Tardy  Y., , Mooser  V., , Nussberger  J., , Waeber  B., , and Brunner  H. R., “ Conduit artery compliance and distensibility are not necessarily reduced in hypertension. ,” Hypertension. 20, (1 ), 1–6  ((1992)).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.