光谱学与光谱分析 |
|
|
|
|
|
Evaluation of Kinematic Capability of Different Groups by Detecting Oxygen Saturation of Muscle Using Near Infrared Spectroscopy |
LI Yue1, QI He-bin2*, SHI Ji-zhao2, TENG Yi-chao1, DING Hai-shu1 |
1. Department of Biomedical Engineering, Medical School, Tsinghua University, Beijing 100084, China 2. Peking Union Medical College Hospital, Beijing 100730, China |
|
|
Abstract Based on the principles of organizational optics, the noninvasive tissue oxygenation saturation monitor was developed. The monitor was used to continuously monitor the changes in regional oxygen index of the thigh vastus lateralis in 101 volunteers, who performed an incremental intensity exercise on bicycle ergometer. Among the volunteers, 42 are athletes, 25 are patients whose spleens are asthenic, and the other 34 are controls. Hemoglobin concentration (ctHb) measured was heavily influenced by the thickness of fattiness; however, regional oxygen saturation (rSO2) was influenced much lightly. In the experiment, following increasing exercise intensity of the volunteers, their ctHb increased, while their rSO2 decreased. When the volunteers stopped the exercise, both of their ctHb and rSO2 increased quickly. The results showed that the regional saturation of oxygen of muscle was closely correlated with physical performance. The changes of regional saturation of oxygen of muscle can be used to evaluate the balance between supply and consumption of oxygen, and quantitatively assess the capability of oxidative metabolism in muscles.
|
Received: 2009-02-22
Accepted: 2009-05-26
|
|
Corresponding Authors:
QI He-bin
E-mail: liyue01@mails.tsinghua.edu.cn
|
|
[1] LIU You-zhang, WANG Chang-jun, ZHOU Jun-liang, et al(刘友章,王昌俊,周俊亮,等). Chinese Achieves of Traditional Chinese Medicine(中医药学刊),2006,24(3):391. [2] Jobsis F F. Science, 1977, 198: 1264. [3] Usaj A, Jereb B, Robi P, et al. European Journal of Applied Physiology, 2007, 100(6): 685. [4] DiMenna Fred J, Wilkerson Daryl P, Burnley Mark, et al. Journal of Applied Physiology, 2009, 106: 432. [5] Ferreira Leonardo F, Koga Shunsaku,Barstow Thomas J. Journal of Applied Physiology, 2007, 103: 1999. [6] XU Guo-dong, CHEN Si, LIU Fang, et al(徐国栋,陈 思,刘 方,等). Journal of Wuhan Institute of Physical Education(武汉体育学院学报), 2003, 37(2): 40. [7] XU Xiang-feng, SHEN You-qing(徐祥峰,沈友清),Journal of Capital Institute of Physical Education(首都体育学院学报),2007, 19(1): 54. [8] XU Guo-dong, LUO Qing-ming(徐国栋,骆清铭). Journal of Wuhan Institute of Physical Education(武汉体育学院学报),2001, 35(3): 40. [9] XU Guo-dong, ZHOU Chao-yan, LIU Chong-xin, et al(徐国栋,周超彦,刘重新,等). Journal of Shandong Institute of Physical Education(山东体育学院学报),2004,20(2):37. [10] XU Guo-dong, ZHOU Chao-yan, GONG Hui, et al(徐国栋,周超彦,龚 辉,等). Journal of Wuhan Institute of Physical Education(武汉体育学院学报),2004,38(4):68. [11] WANG Rong-hui, LIU Gui-hua, ZHANG Yi-min, et al(王荣辉,刘桂华,张一民,等). Journal of Beijing Institute of Physical Education(北京体育大学学报),2001,24 (3): 326. [12] DING Haishu, WANG Guangzhi, LI Wei, et al. J. Sports. Med., 2001, 35: 441. [13] WANG Rong-hui, LIU Gui-hua, ZHANG Yi-min, et al(王荣辉,刘桂华,张一民,等). Journal of Beijing Institute of Physical Education(北京体育大学学报),2002,25(5):630. [14] DING Hai-shu, WANG Guang-zhi(丁海曙,王广志). Modern Rehabilitation(现代康复),2000,4(5): 653. [15] Niwayama M, Hamaoka T, Lin L, et al. SPIE, 2000, 3911: 256. [16] Susumu Suzuki, Sumio Takasaki, Takeo Ozaki, et al. Proc. SPIE, 1999, 3597: 582. [17] XU Chang-hui, GAO Hong-bo, SHI Yao-xun, et al(徐长辉,高洪波,史耀勋,等). World Journal of Integrated Traditional and Western Medicine(世界中西医结合杂志),2008, 3(10): 611.
|
[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. |
|
|
|
|