Abstract

Recent advances in the development of ultra-compact semiconductor lasers and technology of printed flexible hybrid electronics have opened broad perspectives for the design of new pulse oximetry and photoplethysmography devices. Conceptual design of optical diagnostic devices requires careful selection of various technical parameters, including spectral range; polarization and intensity of incident light; actual size, geometry, and sensitivity of the detector; and mutual position of the source and detector on the surface of skin. In the current study utilizing a unified Monte Carlo computational tool, we explore the variations in diagnostic volume due to arterial blood pulsation for typical transmitted and back-scattered probing configurations in a human finger. The results of computational studies show that the variations in diagnostic volumes due to arterial pulse wave are notably (up to 45%) different in visible and near-infrared spectral ranges in both transmitted and back-scattered probing geometries. While these variations are acceptable for relative measurements in pulse oximetry and/or photoplethysmography, for absolute measurements, an alignment normalization of diagnostic volume is required and can be done by a computational approach utilized in the framework of the current study.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article

Corrections

26 November 2019: Corrections were made to the author listing, body and funding sections.


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References

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2019 (4)

E. Zherebtsov, V. Dremin, A. Popov, A. Doronin, D. Kurakina, M. Kirillin, I. Meglinski, and A. Bykov, “Hyperspectral imaging of human skin aided by artificial neural networks,” Biomed. Opt. Express 10, 3545–3559 (2019).
[Crossref]

E. A. Zherebtsov, E. V. Zharkikh, I. Kozlov, A. I. Zherebtsova, Y. I. Loktionova, N. B. Chichkov, I. E. Rafailov, V. V. Sidorov, S. G. Sokolovski, A. V. Dunaev, and E. U. Rafailov, “Novel wearable VCSEL-based sensors for multipoint measurements of blood perfusion,” Proc. SPIE 10877, 1087708 (2019).
[Crossref]

V. Dremin, I. Kozlov, M. Volkov, N. Margaryants, A. Potemkin, E. Zherebtsov, A. Dunaev, and I. Gurov, “Dynamic evaluation of blood flow microcirculation by combined use of the laser Doppler flowmetry and high-speed videocapillaroscopy methods,” J. Biophoton. 12, e201800317 (2019).
[Crossref]

I. Mizeva, E. V. Potapova, V. V. Dremin, E. A. Zherebtsov, M. A. Mezentsev, V. V. Shupletsov, and A. V. Dunaev, “Optical probe pressure effects on cutaneous blood flow,” Clin. Hemorheol. Microcirc. 72, 259–267 (2019).
[Crossref]

2018 (4)

I. Mizeva, E. Zharkikh, V. Dremin, E. Zherebtsov, I. Makovik, E. Potapova, and A. Dunaev, “Spectral analysis of the blood flow in the foot microvascular bed during thermal testing in patients with diabetes mellitus,” Microvasc. Res. 120, 13–20 (2018).
[Crossref]

C. E. Dunn, B. Lertsakdadet, C. Crouzet, A. Bahani, and B. Choi, “Comparison of speckleplethysmographic (SPG) and photoplethysmographic (PPG) imaging by Monte Carlo simulations and in vivo measurements,” Biomed. Opt. Express 9, 4306–4316 (2018).
[Crossref]

A. V. Moço, S. Stuijk, and G. de Haan, “New insights into the origin of remote PPG signals in visible light and infrared,” Sci. Rep. 8, 8501 (2018).
[Crossref]

Y. Masuda, Y. Ogura, Y. Inagaki, T. Yasui, and Y. Aizu, “Analysis of the influence of collagen fibres in the dermis on skin optical reflectance by Monte Carlo simulation in a nine-layered skin model,” Skin Res. Technol. 24, 248–255 (2018).
[Crossref]

2017 (3)

M. V. Volkov, N. B. Margaryants, A. V. Potemkin, M. A. Volynsky, I. P. Gurov, O. V. Mamontov, and A. A. Kamshilin, “Video capillaroscopy clarifies mechanism of the photoplethysmographic waveform appearance,” Sci. Rep. 7, 13298 (2017).
[Crossref]

I. Mizeva, I. Makovik, A. Dunaev, A. Krupatkin, and I. Meglinski, “Analysis of skin blood microflow oscillations in patients with rheumatic diseases,” J. Biomed. Opt. 22, 070501 (2017).
[Crossref]

A. P. Popov, A. V. Bykov, and I. V. Meglinski, “Influence of probe pressure on diffuse reflectance spectra of human skin measured in vivo,” J. Biomed. Opt. 22, 110504 (2017).
[Crossref]

2016 (1)

Y. Sun and N. Thakor, “Photoplethysmography revisited: from contact to noncontact, from point to imaging,” IEEE Trans. Biomed. Eng. 63, 463–477 (2016).
[Crossref]

2015 (2)

A. Dunaev, V. Dremin, E. Zherebtsov, I. Rafailov, K. Litvinova, S. Palmer, N. Stewart, S. Sokolovski, and E. Rafailov, “Individual variability analysis of fluorescence parameters measured in skin with different levels of nutritive blood flow,” Med. Eng. Phys. 37, 574–583 (2015).
[Crossref]

A. A. Kamshilin, E. Nippolainen, I. S. Sidorov, P. V. Vasilev, N. P. Erofeev, N. P. Podolian, and R. V. Romashko, “A new look at the essence of the imaging photoplethysmography,” Sci. Rep. 5, 10494 (2015).
[Crossref]

2014 (4)

M. Nitzan, A. Romem, and R. Koppel, “Pulse oximetry: fundamentals and technology update,” Med. Dev. Evidence Res. 7, 231–239 (2014).
[Crossref]

G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 10901–10924 (2014).
[Crossref]

A. V. Dunaev, V. V. Sidorov, A. I. Krupatkin, I. E. Rafailov, S. G. Palmer, N. A. Stewart, S. G. Sokolovski, and E. U. Rafailov, “Investigating tissue respiration and skin microhaemocirculation under adaptive changes and the synchronization of blood flow and oxygen saturation rhythms,” Physiol. Meas. 35, 607–621 (2014).
[Crossref]

N. Bosschaart, G. J. Edelman, M. C. G. Aalders, T. G. van Leeuwen, and D. J. Faber, “A literature review and novel theoretical approach on the optical properties of whole blood,” Laser Med. Sci. 29,453–479 (2014).
[Crossref]

2013 (2)

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R61 (2013).
[Crossref]

I. V. Meglinski, V. V. Kalchenko, Y. L. Kuznetsov, B. I. Kuznik, and V. V. Tuchin, “Towards the nature of biological zero in the dynamic light scattering diagnostic modalities,” Dokl. Phys. 58, 323–326 (2013).
[Crossref]

2012 (1)

2011 (3)

A. Doronin and I. Meglinski, “Online object oriented Monte Carlo computational tool for the needs of biomedical optics,” Biomed. Opt. Express 2, 2461–2469 (2011).
[Crossref]

A. Doronin, I. Fine, and I. Meglinski, “Assessment of the calibration curve for transmittance pulse-oximetry,” Laser Phys. 21, 1972–1977 (2011).
[Crossref]

A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: a review,” J. Innov. Opt. Health Sci. 04, 9–38 (2011).
[Crossref]

2010 (1)

M. J. Leahy and G. E. Nilsson, “Laser Doppler flowmetry for assessment of tissue microcirculation: 30 years to clinical acceptance,” Proc. SPIE 7563, 75630E (2010).
[Crossref]

2009 (2)

G. Zonios and A. Dimou, “Light scattering spectroscopy of human skin in vivo,” Opt. Express 17, 1256–1267 (2009).
[Crossref]

C. E. Thorn, S. J. Matcher, I. V. Meglinski, and A. C. Shore, “Is mean blood saturation a useful marker of tissue oxygenation?” Am. J. Physiol. Heart Circ. Physiol. 296, H1289–H1295 (2009).
[Crossref]

2008 (1)

S.-H. Tseng, A. Grant, and A. J. Durkin, “In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy,” J. Biomed. Opt. 13, 014016 (2008).
[Crossref]

2007 (2)

A. A. Kokhanovsky, “Physical interpretation and accuracy of the Kubelka-Munk theory,” J. Phys. D 40, 2210–2216 (2007).
[Crossref]

C. E. East and P. B. Colditz, “Intrapartum oximetry of the fetus,” Anesth. Analg. 105, S59–S65 (2007).
[Crossref]

2006 (2)

E. Salomatina, B. Jiang, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
[Crossref]

H. Ding, J. Q. Lu, W. A. Wooden, P. J. Kragel, X.-H. Hu, and X. Hu, “Refractive indices of human skin tissues at eight wavelengths and estimated dispersion relations between 300 and 1600  nm,” Phys. Med. Biol. 51, 1479–1489 (2006).
[Crossref]

2005 (1)

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50, 4225–4241 (2005).
[Crossref]

2004 (3)

G. Zonios, U. Shankar, and V. K. Iyer, “Pulse oximetry theory and calibration for low saturations,” IEEE Trans. Biomed. Eng. 51, 818–822 (2004).
[Crossref]

A. Pifferi, A. Torricelli, P. Taroni, A. Bassi, E. Chikoidze, E. Giambattistelli, and R. Cubeddu, “Optical biopsy of bone tissue: a step toward the diagnosis of bone pathologies,” J. Biomed. Opt. 9, 474–480 (2004).
[Crossref]

N. Ugryumova, S. J. Matcher, and D. P. Attenburrow, “Measurement of bone mineral density via light scattering,” Phys. Med. Biol. 49, 469–483 (2004).
[Crossref]

2002 (2)

S. J. Matcher and I. V. Meglinski, “Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,” Physiol. Meas. 23, 741–753 (2002).
[Crossref]

I. V. Meglinskii, A. N. Bashkatov, E. A. Genina, D. Y. Churmakov, and V. V. Tuchin, “Study of the possibility of increasing the probing depth by the method of reflection confocal microscopy upon immersion clearing of near-surface human skin layers,” Quantum Electron. 32, 875–882 (2002).
[Crossref]

2001 (2)

I. V. Meglinsky and S. J. Matcher, “Modelling the sampling volume for skin blood oxygenation measurements,” Med. Biol. Eng. Comput. 39, 44–50 (2001).
[Crossref]

I. V. Meglinski and S. D. Matcher, “Analysis of the spatial distribution of detector sensitivity in a multilayer randomly inhomogeneous medium with strong light scattering and absorption by the Monte Carlo method,” Opt. Spectrosc. 91, 654–659 (2001).
[Crossref]

1999 (1)

A. Stefanovska, M. Bracic, and H. D. Kvernmo, “Wavelet analysis of oscillations in the peripheral blood circulation measured by laser Doppler technique,” IEEE Trans. Biomed. Eng. 46, 1230–1239 (1999).
[Crossref]

1995 (1)

1993 (1)

1989 (1)

M. J. van Gemert, S. L. Jacques, H. J. Sterenborg, and W. M. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36, 1146–1154 (1989).
[Crossref]

Aalders, M. C. G.

N. Bosschaart, G. J. Edelman, M. C. G. Aalders, T. G. van Leeuwen, and D. J. Faber, “A literature review and novel theoretical approach on the optical properties of whole blood,” Laser Med. Sci. 29,453–479 (2014).
[Crossref]

Aarnoudse, J. G.

R. Graaff, A. C. M. Dassel, W. G. Zijlstra, F. F. M. de Mul, and J. G. Aarnoudse, “How tissue optics influences reflectance pulse oximetry,” in Advances in Experimental Medicine and Biology (Plenum, 1996), Vol. 388, pp. 117–132.

Aizu, Y.

Y. Masuda, Y. Ogura, Y. Inagaki, T. Yasui, and Y. Aizu, “Analysis of the influence of collagen fibres in the dermis on skin optical reflectance by Monte Carlo simulation in a nine-layered skin model,” Skin Res. Technol. 24, 248–255 (2018).
[Crossref]

Alexandrakis, G.

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50, 4225–4241 (2005).
[Crossref]

Attenburrow, D. P.

N. Ugryumova, S. J. Matcher, and D. P. Attenburrow, “Measurement of bone mineral density via light scattering,” Phys. Med. Biol. 49, 469–483 (2004).
[Crossref]

Bahani, A.

Bashkatov, A.

I. Meglinski, A. Doronin, A. Bashkatov, E. Genina, and V. Tuchin, “Dermal component–based optical modeling of skin translucency: impact on skin color,” in Computational Biophysics of the Skin (Pan Stanford, 2014), pp. 25–61.

Bashkatov, A. N.

A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: a review,” J. Innov. Opt. Health Sci. 04, 9–38 (2011).
[Crossref]

I. V. Meglinskii, A. N. Bashkatov, E. A. Genina, D. Y. Churmakov, and V. V. Tuchin, “Study of the possibility of increasing the probing depth by the method of reflection confocal microscopy upon immersion clearing of near-surface human skin layers,” Quantum Electron. 32, 875–882 (2002).
[Crossref]

Bassi, A.

A. Pifferi, A. Torricelli, P. Taroni, A. Bassi, E. Chikoidze, E. Giambattistelli, and R. Cubeddu, “Optical biopsy of bone tissue: a step toward the diagnosis of bone pathologies,” J. Biomed. Opt. 9, 474–480 (2004).
[Crossref]

Bosschaart, N.

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V. Dremin, I. Kozlov, M. Volkov, N. Margaryants, A. Potemkin, E. Zherebtsov, A. Dunaev, and I. Gurov, “Dynamic evaluation of blood flow microcirculation by combined use of the laser Doppler flowmetry and high-speed videocapillaroscopy methods,” J. Biophoton. 12, e201800317 (2019).
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E. Zherebtsov, V. Dremin, A. Popov, A. Doronin, D. Kurakina, M. Kirillin, I. Meglinski, and A. Bykov, “Hyperspectral imaging of human skin aided by artificial neural networks,” Biomed. Opt. Express 10, 3545–3559 (2019).
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Meglinski, I. V.

A. P. Popov, A. V. Bykov, and I. V. Meglinski, “Influence of probe pressure on diffuse reflectance spectra of human skin measured in vivo,” J. Biomed. Opt. 22, 110504 (2017).
[Crossref]

I. V. Meglinski, V. V. Kalchenko, Y. L. Kuznetsov, B. I. Kuznik, and V. V. Tuchin, “Towards the nature of biological zero in the dynamic light scattering diagnostic modalities,” Dokl. Phys. 58, 323–326 (2013).
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[Crossref]

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[Crossref]

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I. V. Meglinskii, A. N. Bashkatov, E. A. Genina, D. Y. Churmakov, and V. V. Tuchin, “Study of the possibility of increasing the probing depth by the method of reflection confocal microscopy upon immersion clearing of near-surface human skin layers,” Quantum Electron. 32, 875–882 (2002).
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I. V. Meglinsky and S. J. Matcher, “Modelling the sampling volume for skin blood oxygenation measurements,” Med. Biol. Eng. Comput. 39, 44–50 (2001).
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I. Mizeva, E. V. Potapova, V. V. Dremin, E. A. Zherebtsov, M. A. Mezentsev, V. V. Shupletsov, and A. V. Dunaev, “Optical probe pressure effects on cutaneous blood flow,” Clin. Hemorheol. Microcirc. 72, 259–267 (2019).
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I. Mizeva, E. V. Potapova, V. V. Dremin, E. A. Zherebtsov, M. A. Mezentsev, V. V. Shupletsov, and A. V. Dunaev, “Optical probe pressure effects on cutaneous blood flow,” Clin. Hemorheol. Microcirc. 72, 259–267 (2019).
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Am. J. Physiol. Heart Circ. Physiol. (1)

C. E. Thorn, S. J. Matcher, I. V. Meglinski, and A. C. Shore, “Is mean blood saturation a useful marker of tissue oxygenation?” Am. J. Physiol. Heart Circ. Physiol. 296, H1289–H1295 (2009).
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Appl. Opt. (2)

Biomed. Opt. Express (4)

Clin. Hemorheol. Microcirc. (1)

I. Mizeva, E. V. Potapova, V. V. Dremin, E. A. Zherebtsov, M. A. Mezentsev, V. V. Shupletsov, and A. V. Dunaev, “Optical probe pressure effects on cutaneous blood flow,” Clin. Hemorheol. Microcirc. 72, 259–267 (2019).
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Dokl. Phys. (1)

I. V. Meglinski, V. V. Kalchenko, Y. L. Kuznetsov, B. I. Kuznik, and V. V. Tuchin, “Towards the nature of biological zero in the dynamic light scattering diagnostic modalities,” Dokl. Phys. 58, 323–326 (2013).
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IEEE Trans. Biomed. Eng. (4)

Y. Sun and N. Thakor, “Photoplethysmography revisited: from contact to noncontact, from point to imaging,” IEEE Trans. Biomed. Eng. 63, 463–477 (2016).
[Crossref]

A. Stefanovska, M. Bracic, and H. D. Kvernmo, “Wavelet analysis of oscillations in the peripheral blood circulation measured by laser Doppler technique,” IEEE Trans. Biomed. Eng. 46, 1230–1239 (1999).
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G. Zonios, U. Shankar, and V. K. Iyer, “Pulse oximetry theory and calibration for low saturations,” IEEE Trans. Biomed. Eng. 51, 818–822 (2004).
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J. Biomed. Opt. (6)

A. Pifferi, A. Torricelli, P. Taroni, A. Bassi, E. Chikoidze, E. Giambattistelli, and R. Cubeddu, “Optical biopsy of bone tissue: a step toward the diagnosis of bone pathologies,” J. Biomed. Opt. 9, 474–480 (2004).
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I. Mizeva, I. Makovik, A. Dunaev, A. Krupatkin, and I. Meglinski, “Analysis of skin blood microflow oscillations in patients with rheumatic diseases,” J. Biomed. Opt. 22, 070501 (2017).
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Supplementary Material (2)

NameDescription
» Visualization 1       Sampling volume for the back-scattered diffuse reflectance probe.
» Visualization 2       Sampling volume obtained for the transmittance configuration of the source and detector.

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Figures (5)

Fig. 1.
Fig. 1. (a) Absorption coefficients of tissue layers: 1–Stratum corneum, 2–epidermis, 3–papillary dermis, 4–upper blood net dermis, 5–reticular dermis, 6–deep blood net dermis, 7–subcutaneous tissue. (b) Scattering coefficients: 1–Stratum corneum, 2–epidermis, 3–dermis, 4–subcutaneous fat. (c) Scattering anisotropy factor: numerical designations correspond to the designations described for the absorption coefficients. (d) Refractive index: numerical designations correspond to the designations described for the scattering coefficients. Optical properties were derived from a number of sources described in the text.
Fig. 2.
Fig. 2. Typical layout of diffuse (a) reflectance and (b) transmittance measurements and skin tissue layers; (c) PPG function of changes in the arterial layer thickness taken into account in the MC model.
Fig. 3.
Fig. 3. Sampling volume for the back-scattered diffuse reflectance probe, schematically presented in Fig. 2(a). The wavelengths of light used in the modeling are: (a) 940 nm, (b) 860 nm, (c) 800 nm, (d) 660 nm, (e) 532 nm, and (f) 450 nm (see Visualization 1).
Fig. 4.
Fig. 4. (a) Relative changes in sampling volume distribution for different light wavelengths during the arterial wave pulse period; (b) light penetration depth at $ {10^{ - 3}} $ of the incident light intensity.
Fig. 5.
Fig. 5. Sampling volume obtained for the transmittance configuration of the source and detector, schematically presented in Fig. 2(b) for the wavelengths (a) 660 nm and (b) 940 nm (see Visualization 2). (c) Relative changes in sampling volume.

Tables (2)

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Table 1. Parameters of the Diffuse Reflectance Model [30,36,39]

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Table 2. Parameters of the Diffuse Transmittance Model

Equations (4)

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Q ( r ) = μ a ( r ) l n ( I I 0 ) ,
Q ( r ) = μ a ( r ) l n ( I I 0 ) = i = 1 N p h l i ( r ) W d i l 0 i = 1 N p h W d i ,
W d = W 0 exp ( k μ a k l k ) .
μ a ( λ ) = i C i μ a i ( λ ) .

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