光电容积脉搏信号的光学特征建模研究——血容量、红细胞与血管壁模型的耦合作用机制
Optical Feature Modeling of Photoplethysmographic Signals—Coupling Mechanisms of Blood Volume, Red Blood Cell, and Vascular Wall Models
DOI: 10.12677/mos.2025.145392, PDF,   
作者: 李 凯:上海理工大学健康科学与工程学院,上海;孙九爱*:上海健康医学院附属上海市嘉定区中心医院医学影像科,上海
关键词: 光电容积脉搏波光学特征模型血容量红细胞血管壁Photoplethysmography Optical Feature Model Blood Volume Red Blood Cell Vascular Wall
摘要: 光电容积脉搏描计法(Photoplethysmography, PPG)是一种无创技术,广泛应用于心率、血氧饱和度等生理参数的监测。然而,PPG信号的生成机制尚未完全明确。现有的血容量模型、红细胞模型以及近年来提出的血管壁运动模型均无法全面解释在不同解剖部位和检测条件下观察到的PPG信号变化。为此,本研究提出并验证了一种综合光学模型,该模型结合了血容量、红细胞和血管壁的影响,能够更全面地解释PPG信号的生成机制。为验证该模型的有效性,本研究开发了一套定制的多光谱PPG信号采集平台,采集了20名健康参与者左手食指远节和中节指节区域的PPG信号。实验结果表明,不同解剖部位和光谱通道PPG信号的脉动分量存在显著差异。通过定量分析各模型因素对PPG信号的贡献,验证了综合光学模型在解释这些差异方面的有效性和普适性,表明其可用于不同解剖部位的PPG信号分析,并为生理参数监测提供了新的理论支持。
Abstract: Photoplethysmography (PPG) is a noninvasive technique widely used for monitoring physiological parameters such as heart rate and blood oxygen saturation. However, the signal generation mechanism of PPG remains incompletely understood. Existing models—including the blood volume model, red blood cell model, and the recently proposed vascular wall model—fail to comprehensively explain PPG signal variations observed across different anatomical sites and measurement conditions. To address this, we propose and validate a comprehensive optical model that integrates the effects of blood volume, red blood cells, and vascular wall dynamics, providing a more complete explanation of PPG signal generation. To validate the model, we developed a custom multi-spectral PPG acquisition platform and collected signals from the distal and middle phalanges of the left index fingers of 20 healthy participants. Experimental results demonstrate significant differences in the pulsatile components of PPG signals across anatomical sites and spectral channels. A quantitative analysis of the contributions of each factor in the model confirms its validity and generalizability in explaining these variations. This comprehensive model enhances the understanding of PPG signal generation across various anatomical regions and provides a stronger theoretical foundation for improving physiological parameter monitoring.
文章引用:李凯, 孙九爱. 光电容积脉搏信号的光学特征建模研究——血容量、红细胞与血管壁模型的耦合作用机制[J]. 建模与仿真, 2025, 14(5): 272-281. https://doi.org/10.12677/mos.2025.145392

参考文献

[1] Allen, J. (2007) Photoplethysmography and Its Application in Clinical Physiological Measurement. Physiological Measurement, 28, R1-R39. [Google Scholar] [CrossRef] [PubMed]
[2] Moço, A.V., Stuijk, S. and de Haan, G. (2018) New Insights into the Origin of Remote PPG Signals in Visible Light and Infrared. Scientific Reports, 8, Article No. 8501. [Google Scholar] [CrossRef] [PubMed]
[3] Fine, I. and Kaminsky, A. (2022) Scattering-Driven PPG Signal Model. Biomedical Optics Express, 13, 2286-2298. [Google Scholar] [CrossRef] [PubMed]
[4] Kamshilin, A.A. and Margaryants, N.B. (2017) Origin of Photoplethysmographic Waveform at Green Light. Physics Procedia, 86, 72-80. [Google Scholar] [CrossRef
[5] Kamshilin, A.A. and Mamontov, O.V. (2022) Physiological Origin of Camera-Based PPG Imaging. In: Contactless Vital Signs Monitoring, Elsevier, 27-50. [Google Scholar] [CrossRef
[6] Fein, M.E. (1997) Evaluation of Optical Methods of Detecting Dental Pulp Vitality. Journal of Biomedical Optics, 2, 58. [Google Scholar] [CrossRef] [PubMed]
[7] Binzoni, T., Tchernin, D., Hyacinthe, J., Van De Ville, D. and Richiardi, J. (2013) Pulsatile Blood Flow in Human Bone Assessed by Laser-Doppler Flowmetry and the Interpretation of Photoplethysmographic Signals. Physiological Measurement, 34, N25-N40. [Google Scholar] [CrossRef] [PubMed]
[8] Kyriacou, P.A. (2022) Introduction to Photoplethysmography. In: Photoplethysmography, Elsevier, 1-16. [Google Scholar] [CrossRef
[9] Zaunseder, S., Trumpp, A., Wedekind, D. and Malberg, H. (2018) Cardiovascular Assessment by Imaging Photoplethysmography—A Review. Biomedical Engineering, 63, 617-634. [Google Scholar] [CrossRef] [PubMed]
[10] Li, K. and Sun, J. (2024) Understanding the Physiological Transmission Mechanisms of Photoplethysmography Signals: A Comprehensive Review. Physiological Measurement, 45, 08TR02. [Google Scholar] [CrossRef] [PubMed]
[11] Rybynok, V.O. and Kyriacou, P.A. (2010) Beer-Lambert Law along Non-Linear Mean Light Pathways for the Rational Analysis of Photoplethysmography. Journal of Physics: Conference Series, 238, Article 012061. [Google Scholar] [CrossRef
[12] Nitzan, M., Nitzan, I. and Arieli, Y. (2020) The Various Oximetric Techniques Used for the Evaluation of Blood Oxygenation. Sensors, 20, Article 4844. [Google Scholar] [CrossRef] [PubMed]
[13] Shvartsman, L.D. and Fine, I. (2001) Light-Scattering Changes Caused by RBC Aggregation: Physical Basis for New Approach to Noninvasive Blood Count. SPIE Proceedings, San Jose, 20 January 2001, 131-142. [Google Scholar] [CrossRef
[14] Fine, I. (2014) The Optical Origin of the PPG Signal. SPIE Proceedings, Saratov, 24 September 2013, Article 903103. [Google Scholar] [CrossRef
[15] Kamshilin, A.A., Zaytsev, V.V. and Mamontov, O.V. (2017) Novel Contactless Approach for Assessment of Venous Occlusion Plethysmography by Video Recordings at the Green Illumination. Scientific Reports, 7, Article No. 464. [Google Scholar] [CrossRef] [PubMed]
[16] Miao, Q.R., Wang, H.X., Yu, Y. and Zhang, Y.L. (2023) Application of Optical Coherence Tomography in Fingertip Biometrics. Laser & Optoelectronics Progress, 60, Article 0811012.
[17] Anderson, R.R. and Parrish, J.A. (1982) Optical Properties of Human Skin. In: The Science of Photomedicine, Springer, 147-194. [Google Scholar] [CrossRef
[18] Nitzan, M. and Ovadia-Blechman, Z. (2022) Physical and Physiological Interpretations of the PPG Signal. In: Photoplethysmography, Elsevier, 319-340. [Google Scholar] [CrossRef
[19] Sidorov, I.S., Romashko, R.V., Koval, V.T., Giniatullin, R. and Kamshilin, A.A. (2016) Origin of Infrared Light Modulation in Reflectance-Mode Photoplethysmography. PLOS ONE, 11, e0165413. [Google Scholar] [CrossRef] [PubMed]
[20] Volkov, M.V., Margaryants, N.B., Potemkin, A.V., Volynsky, M.A., Gurov, I.P., Mamontov, O.V., et al. (2017) Video Capillaroscopy Clarifies Mechanism of the Photoplethysmographic Waveform Appearance. Scientific Reports, 7, Article No. 13298. [Google Scholar] [CrossRef] [PubMed]
[21] Wang, T. and Xing, Z. (2010) Characterization of Blood Flow in Capillaries by Numerical Simulation. Journal of Modern Physics, 1, 349-356. [Google Scholar] [CrossRef