| 光谱学与光谱分析 |
|
|
|
|
|
| Near-Infrared Spectral Study on Blood Oxygen Saturation in Multilayer Tissue |
| GAO Bo1，WEI Wei2，GONG Min1*，WANG Li2 |
1. School of Physical Science and Technology, Sichuan University, Sichuan Province Key Laboratory of Microelectronics, Chengdu 610064, China
2. Department of Anesthesiology and Critical Ill Medicine, West China Hospital, Sichuan University, Chengdu 610041, China |
|
|
|
|
Abstract The technology of non-invasive near-infrared spectral detection of biological tissue blood oxygen saturation has great research and application prospects, and has widespread clinical applications. However, the conventional finger oximeter only reflects local oxygen saturation values, and has limitations in the application. These oxygenation readings become unreliable or cease, too. In the present paper, a new method is described that the reflectance pulse oximetry with variable incident light intensity is employed to measure biological multilayer tissue. The photoplethysmographic (PPG) signals significantly change with the change in the incident light intensity in the experiment on the fingertip. Further analysis shows that the changes of the PPG signals correspond to the multilayer structure of finger. It means that the blood oxygen saturation of different tissue level must be calculated from the PPG signals. These features show that this method must be feasible.
|
|
Received: 2008-11-18
Accepted: 2009-02-22
|
|
|
|
Corresponding Authors:
GONG Min
E-mail: mgong@scu.edu.cn
|
|
[1] Kurth C D, Steven J M, Swedlow D. Am. J. Anesthesiol., 1996, 23: 169.
[2] ZHUANG Xin-liang, ZENG Yin-ming, CHEN Bo-luan(庄心良，曾因明，陈伯銮). Modern Anesthesiology(现代麻醉学). Beijing: People’s Medical Publishing House(北京：人民卫生出版社)，2003.
[3] Wei Wei, Zhu Zhaoqiong, Liu Lunxu, et al. Anesth. Analog, 2005, 101: 440.
[4] Kyriacou P A, Crerar-Gilber A, Langford R M, et al. Journal of Physics: Conference Series，2006, 45: 232.
[5] Crerar-Gilbert A, Kyriacou P A, Jones D P, et al. Anaesthesia, 2002, 57：442.
[6] ZHU Zhao-qiong, WEI Wei, XUE Fu-shan, et al(朱昭琼，魏 蔚，薛福善，等). Journal of Clinical Anesthesiology(临床麻醉学杂志)，2006，21(10)：670.
[7] Webster J G. Design of Pulse Oximeters. Bristol: Institute of Physics Publishing, 1997.
[8] Nijboer J A，Dorlas J C，Mahieu H F. Clin. Phys. Physiol. Meas., 1981, 2(3): 205.
[9] Mannheimer P D, Casciani J R, Fein M E，et al. IEEE Trans. Biomed. Eng, 1997, 44：148.
[10] Moyle J T B. Principles and Practice Series: Pulse Oximetry. London: BMJ Publishing Group, 1994.
[11] Cormack G C，et al. The Arterial Anatomy of Skin Flaps. Churchill Livingstone, 1994.
[12] Burr-Brown Corporation, DDC112 Hardware Guide, 2000.
[13] Reuss James L. IEEE Transactions on Biomedical Engineering, 2005, 52(2)：153.
[14] Haahr Rasmus G, Duun Sune，et al. Proceedings of the 29th Annual International Conference of the IEEE EMBS, 2007. 2350.
[15] Dresher R P，Mendelson Y. IEEE Bioengineering Conference, 2006. 49. |
| [1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [2] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [3] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [4] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [5] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [6] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [7] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
| [8] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
| [9] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
| [10] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
| [11] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [12] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
| [13] |
HUANG Hua1, LIU Ya2, KUERBANGULI·Dulikun1, ZENG Fan-lin1, MAYIRAN·Maimaiti1, AWAGULI·Maimaiti1, MAIDINUERHAN·Aizezi1, GUO Jun-xian3*. Ensemble Learning Model Incorporating Fractional Differential and
PIMP-RF Algorithm to Predict Soluble Solids Content of Apples
During Maturing Period[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3059-3066. |
| [14] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
| [15] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
|
|
|
|
