无创血糖检测中的近红外血流容积光谱基本问题研究
|
摘要
糖尿病是最常见的慢性疾病,严重威胁人类健康。目前血糖常规检测方法属于有创或微创检测,频繁采血化验会给病人增加痛苦和经济负担,并且无法做到实时监测。近红外光谱血糖检测技术具有无创伤、无感染等优点,对减轻糖尿病患者疼痛、实现血糖浓度的实时监测具有非常重要的现实意义。
本论文总结前人的研究成果,概括出该领域目前面临的关键难题,即:①信号微弱;②组织背景干扰;③血流容积变化。认为采用近红外血流容积差光谱相减法理论上可以扣除生理组织背景在空间和时间域上的干扰,提取出仅含血液成分信息的有效光谱信号。
设计搭建出近红外容积脉搏波检测系统,研究了血流容积光谱相减方法中涉及的基本问题:①通过测试确定了血流容积差光谱相减的最佳检测位置。②通过实验提取出近红外无创血糖分析时合频波段的替代波段。③总结出所采用的光谱仪在时间分辨方面的特殊要求。④通过公式推导估算出给定可检测的最小浓度变化时,近红外光谱仪器重复性信噪比应满足的条件。⑤通过临床测量实验,研究不同年龄、不同疾病患者血流容积脉搏波峰峰值区别。⑥提出阻断血流法,可以有效提高人体血流容积差,进而使达到预期预测精度所需仪器重复性信噪比降低1个数量级。
Diabetes is a common chronic diseases,endanger human health seriously. Currently, conventional testing methods of blood glucose are invasive detection. Thence, frequent blood testing will bring patients unnecessary suffering and economic burden, which makes continuous monitoring unpractical. Near infrared spectroscopy (NIR) glucose detection is an analytical technology with noninvasive, no infection advantages. This technology possesses very important practical significance in alleviating pain of patients and achieving continuous glucose concentration monitoring.
This dissertation summarizes the results of previous studies, and generalizes the currently key challenges which NIR noninvasive glucose detection faces:①weak signal;②interference of tissue background;③blood volume changing. NIR subtracted blood volume spectrometry can deduct the tissue background interference in space and time domain, and obtain effective spectrum information of blood.
A detection system for near-infrared volume wave is built. Some basic problems involved in NIR subtracted blood volume spectrometry are studied.①Determine the best testing location for subtracted blood volume spectrometry.②Propose the substitute band of combination in NIR spectroscopy noninvasive glucose detection.③Propose the time resolution requirements of NIR spectrometer.④Estimate the repeat signal to noise ratio requirements of NIR spectrometer.⑤Investigate differences of pulse peak to peak value between the patients of different ages and different diseases.⑥Propose the vascular occlusion method, which can increase the volume difference of human body blood, and then lower the requirements of the signal to noise ratio for one order of magnitude.
本论文总结前人的研究成果,概括出该领域目前面临的关键难题,即:①信号微弱;②组织背景干扰;③血流容积变化。认为采用近红外血流容积差光谱相减法理论上可以扣除生理组织背景在空间和时间域上的干扰,提取出仅含血液成分信息的有效光谱信号。
设计搭建出近红外容积脉搏波检测系统,研究了血流容积光谱相减方法中涉及的基本问题:①通过测试确定了血流容积差光谱相减的最佳检测位置。②通过实验提取出近红外无创血糖分析时合频波段的替代波段。③总结出所采用的光谱仪在时间分辨方面的特殊要求。④通过公式推导估算出给定可检测的最小浓度变化时,近红外光谱仪器重复性信噪比应满足的条件。⑤通过临床测量实验,研究不同年龄、不同疾病患者血流容积脉搏波峰峰值区别。⑥提出阻断血流法,可以有效提高人体血流容积差,进而使达到预期预测精度所需仪器重复性信噪比降低1个数量级。
Diabetes is a common chronic diseases,endanger human health seriously. Currently, conventional testing methods of blood glucose are invasive detection. Thence, frequent blood testing will bring patients unnecessary suffering and economic burden, which makes continuous monitoring unpractical. Near infrared spectroscopy (NIR) glucose detection is an analytical technology with noninvasive, no infection advantages. This technology possesses very important practical significance in alleviating pain of patients and achieving continuous glucose concentration monitoring.
This dissertation summarizes the results of previous studies, and generalizes the currently key challenges which NIR noninvasive glucose detection faces:①weak signal;②interference of tissue background;③blood volume changing. NIR subtracted blood volume spectrometry can deduct the tissue background interference in space and time domain, and obtain effective spectrum information of blood.
A detection system for near-infrared volume wave is built. Some basic problems involved in NIR subtracted blood volume spectrometry are studied.①Determine the best testing location for subtracted blood volume spectrometry.②Propose the substitute band of combination in NIR spectroscopy noninvasive glucose detection.③Propose the time resolution requirements of NIR spectrometer.④Estimate the repeat signal to noise ratio requirements of NIR spectrometer.⑤Investigate differences of pulse peak to peak value between the patients of different ages and different diseases.⑥Propose the vascular occlusion method, which can increase the volume difference of human body blood, and then lower the requirements of the signal to noise ratio for one order of magnitude.
引文
[1] Jones M,Harrison J M.The future of diabetes technologies and therapeutics[J].Diabetes Technol Ther,2002,4:351-359.
[2]罗云瀚.近红外无创伤血糖浓度测量方法的组织光学基础及应用研究[D].天津大学博士学位论文,2006:3-7.
[3] Cote G L,Cameron B D.Noninvasive polarimertic measurement of glucose in cell culture media[J].J.Biomed.Opt.,1997,2(3):275-281.
[4] Cameron B D,Gorde H,Cote G L.Development of an optical polarimeter for in vivo glucose monitoring[C].Proc.SPIE,1999,3599:43-49.
[5] Berger A J,Koo T W,Itzkan I,et al.Multicomponent blood analysis by near-inrfared Raman spectroscopy[J].Appled Optics,1999,38(13):2916-2926.
[6] Kanger J S . Non-invasive detection of glucose using Raman spectroscopy[C] , Proc.SPIE,1999,3570:123-129.
[7] Larin K V,Motamedi M,Ashitkov T V.Specificity of noninvasive blood glucose sensing using optical coherence tomography technique:a pilot sutdy[J].Phys Med Biol,2003,48(10):1371- 90.
[8] Esenaliev R O,Larin K V,Larina I V.Noninvasive monitoring of glucose concentration with optical coherence tomography[J].Optics Letters,2001,26(13),992-994.
[9] Heise H M.Glucose Measurements by Vibrational Spectroscopy[M].Handbook of Vibrational Spectroscopy, Edited by John M.Chalmers.John Wiley&Sons,LTD,2002:3280-3294.
[10] Arnold M A,Small G W.Noninvasive Glucose Sensing[J].Analytical Chemistry,2005,77(17):5429-5439.
[11] Kim Y J,Hahn S,Yoon G.Detemrination of glucose in whole blood samples bymid-inrfared spectroscopy[J].Applied Optics,2003,42(4):745-749.
[12] Norris K.Possible medical applications of NIR[M].Making light work: Advances in near infrared spectroscopy,Edited by Murray I & Cowe I A.UK:Ian Michael Publication, 1992:596-602.
[13]刘蓉.近红外无创血糖测量一信号构成和拾取的理论及实验研究[D].天津大学博士学位论文,2006:2-3.
[14] Rosenthal R D.A portable non-invasive blood glucose meter[C].Oak-Ridge Conference,1993,312A:1244.
[15] Borchert M S,Storrie-Lombardi M C,Lambert J L.A non-invasive glucose monitor: preliminary results in rabbits[J].Diabetes Technology & Therapeutics,1999,l(2):145-151.
[16] Malin S F,Ruchti T L,Blank T B,et al.Non-invasive Prediction of glucose by near-infrared diffuse reflectance spectroscopy[J].Clinical Chemistry,1999,45:1651-1658.
[17] Peters,Richard K,Elmerick.Non-invasive glucose measuring device and method for measuring blood glucose,USP5,1999,910:109.
[18] Cingo N A,Small G W,Arnold M A,Determination of glucose in a synthetic biological matrix with decimated time-domain filtered near-inrfared inteerfrogram data[J].Vibrational Spectroscopy,2000,23:103-117.
[19] Marbach R,Heise H M.Optical Diffuse Reflectance Accessory for Measurements of Skin Tissue by Near-Infrared Spectroscopy[J],Applied Optics 1995,34:610-621.
[20] Gabriel Y I,Woznia K R,Mevorach M,et al.Transcutaneous glucose measurement using near-infrared spectroscopy during hypoglycemia[J].Diabetes Care,1999,22 (12):2026-2032.
[21] Maruo K,Tsurugi M,Tamura M.In Vivo Noninvasive Measurement of Blood Glucose by Near-Infrared Diffuse-Reflectance Spectroscopy[J].Applied Spectroscopy,2003,57(10):1236-1244.
[22]孙颖,杨展澜,吴瑾光,等.非损伤性血糖检测的研究进展[J].自然科学进展,2002,12(8):806-810.
[23]王炜,卞正中,张大龙.红外多波长无创人体血糖检测阵列模型的研究[J].生物医学工程学杂志,2003,20(4):716-719.
[24]王炜,卞正中,张大龙.红外无创血糖检测与阵列信号处理[J].红外技术,2003,25(2):60-64.
[25] Sun F,Kong D,Mei T,et al.Near infrared spectral methods for non-invasively measuring blood glucose,Proc.SPIE,2004,5281:595-601.
[26]林方,丁海曙,苏畅.Monte-Carlo方法研究生物组织内部光能分布[J].清华大学学报,2000,40(3):20-30.
[27]黄岚,丁海曙,王广志.用近红外漫反射光谱无损检测血糖的初步研究[J].光谱学与光谱分析,2002,22(3):357-391.
[28]沙宪政,李明菊.近红外光谱无创血糖检测技术的研究[J].医疗卫生装备,2003,24(6):29-31.
[29]李明菊,沙宪政.无创性血糖的光谱检测及临床研究状况[J].国外医学生物医学工程分册,2000,23(5):291-299.
[30]马显光,蒲晓允,陈仕国,等.无创血糖仪的研制[J].生物医学工程学杂志,2004,21(3):473-475.
[31] Yamakoshi K,Yamakoshi Y.Pulse glucometry:a new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophoto- metry[J].Journal of Biomedical Optics,2006,11(5):054028.
[32]李刚,李尚颖,林凌,等.基于动态光谱的脉搏血氧测量精度分析[J].光谱学与光谱分析,2006,26(10):1821-1824.
[33]刘蓉,徐可欣,陈文亮,等.光学无创血糖检测中的主要问题及研究进展[J].中国科学G辑:物理学力学天文学,2007,37(增刊):124-131.
[34]陈星旦.近红外光谱无创生化检验的可能性[J].光学精密工程,2008,16(5):759-763.
[35]陆婉珍.现代近红外光谱分析技术(第二版)(M).北京:中国石化出版社,2007:306-333.
[36]严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005.
[37] Williams P , Norris K . Near-Infrared technology in the agricultural and food industries[M], Second Edition, American Association of Cereal Chemists, Inc. 2001.
[38]丁海泉,卢启鹏,朴仁官,等.土壤有机质近红外光谱分析组合波长的优选[J].光学精密工程,2007,15(12):1946-1951.
[39]曹璞,潘涛,陈星旦.小型近红外玉米蛋白质成分分析仪器设计的波段选择[J].光学精密工程,2007,15(12):1952-1959.
[40]张军,陈星旦,朴仁官,等.用于食品成分分析的双探测器近红外光谱仪[J].光学精密工程,2008,16(6):986-992.
[41]陈华才,吕进,陈星旦,等.基于径向基函数网络的茶多酚总儿茶素近红外光谱检测模型的研究[J].光学精密工程,2006,14(1):58-62.
[42]赵强,张工力,陈星旦.多元散射校正对近红外光谱分析定标模型的影响[J].光学精密工程,2005,13(1):53-58.
[43]刘宏欣,张军,黄富荣,等.近红外光谱法快速测定啤酒的主要品质参数[J].光谱学与光谱分析,2008,28(2):313-316.
[44]罗云瀚,陈哲,陈星旦,等.近红外光谱无创血糖测量的极限检测浓度[J].光学精密工程,2008,16(5):784-788.
[45]张军,陈星旦,朴仁官,等.用于食品成分分析的双探测器近红外光谱仪[J].光学精密工程,2008,16(6):986-992.
[46]王动民,金尚忠,陈华才,等.棉-涤混纺面料中棉含量的近红外光谱分析[J].光学精密工程,2008,16(11):2051-2054.
[47]胡愉华,潘涛,陈星旦,等.甘蔗初压汁锤度近红外光谱分析的波段优选[J].光谱实验室,2009,26(1):90-95.
[48]梁家杰,潘涛,陈星旦,等.白砂糖色值近红外光谱分析的波段选择[J].红外技术,2009,31(2):90-94.
[49] Luo Y H,Huang F R,Li S P,et al.Detection limit of glucose concent ration with near-inf rared absorption and scattering spectroscopy[J].Chinese Physics Letters,2008,25 (3):1117-1119.
[50] Luo Y,Cui H,Gu X,et al.Determination of optimal source2detector separation in measuring chromophores in layered tissue with diffuse reflectance[J].Chinese Optics Letters,2005,3 (11):659-661.
[51]梁逸曾.白灰黑复杂多组份分析体系及其化学计量学算法[M].长沙:湖南科学技术出版社,1996:1-10.
[52]王惠文.偏最小二乘回归方法及其应用[M].北京:国防工业出版社,2000:28-110.
[53]柯以侃,董慧茹.分析化学手册第三分册-光谱分析[M].北京:化学工业出版社,1998:176- 177.
[54]罗运平,张军,郑仁富,等.正交信号校正在人体血糖近红外光谱分析中的研究[J].光谱实验室,2007,24(5):773-777.
[55]高荣强,范世福,严衍禄,等.近红外光谱的数据预处理研究[J].光谱学与光谱分析, 2004,12(24):1563-1565.
[56] Anzanello M J,Albin S L,Chaovalitwongse W A.Selecting the best variables for classifying production batches into two quality levels[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):111-117.
[57] Balabin R M,Safieva R Z,Lomakina E I.Wavelet neural network (WNN) approach for calibration model building based on gasoline near infrared (NIR) spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,93(1):58-62.
[58] Billeter J,Neuhold Y-M,Hungerbühler K.Kinetic hard-modelling and spectral validation of rank-deficient spectroscopic data:A case study[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):213-226.
[59] Cai W,Li Y,Shao X.A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,90(2):188-194.
[60] Cui W,Yan X.Adaptive weighted least square support vector machine regression integrated with outlier detection and its application in QSAR[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):130-135.
[61] Devos O,Ruckebusch C,Durand A,et al.Support vector machines (SVM) in near infrared(NIR)spectroscopy: Focus on parameters optimization and model interpret- tation[J].Chemometrics and Intelligent Laboratory Systems,2009,96(1):27-33.
[62] Fearn T, Riccioli C, Garrido-Varo A, et al . On the geometry of SNV and MSC[J].Chemome- trics and Intelligent Laboratory Systems,2009,96(1):22-26.
[63] Benoudjit N,Melgani F,Bouzgou H.Multiple regression systems for spectrophotometric data analysis[J].Chemometrics and Intelligent Laboratory Systems,2009,95(2):144-149.
[64] Bhatt N,Narasimhan S.Multivariate calibration of non-replicated measurements for the factored noise model[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2): 182-194.
[65] Gujral P,Amrhein M,Bonvin D,et al.Classification of magnetic resonance images from rabbit renal perfusion[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):173- 181.
[66] Huang Z,Tao W,Fang J,et al.Multivariate calibration of on-line enrichment near-infrared (NIR) spectra and determination of trace lead in water[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):195-200.
[67] Igne B,Roger J-M,Roussel S,et al.Improving the transfer of near infrared prediction models by orthogonal methods[J].Chemometrics and Intelligent Laboratory Systems,2009,99(1):57- 65.
[68] Kopriva I,Jeric I,Cichocki A.Blind decomposition of infrared spectra using flexible component analysis[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):170- 178.
[69] Liu X,Kruger U,Littler T,et al.Moving window kernel PCA for adaptive monitoring of nonlinear processes[J].Chemometrics and Intelligent Laboratory Systems,2009,96(2):132- 143.
[70] Liu X,Kruger U,Littler T,et al.Moving window kernel PCA for adaptive monitoring of nonlinear processes[J].Chemometrics and Intelligent Laboratory Systems,2009,96(2):132- 143.
[71] Janik L J,Forrester S T,Rawson A.The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis[J].Chemometrics and Intelligent Laboratory Systems,2009, 97(2):179-188.
[72] Kasemsumran S,Du Y P,Maruo K,et al.Improvement of partial least squares models for in vitro and in vivo glucose quantifications by using near-infrared spectroscopy andsearching combination moving window partial least squares[J].Chemometrics and Intelligent Laboratory Systems,2006,82(1-2):97-103.
[73]张玲.PLS定标法在近红外光谱分析仪中的应用研究[J].光学精密工程,2000,8 (3):238- 241.
[74] Kohonen J,Reinikainen S-P,Aaljoki K,et al.Non-linear PLS approach in score surface[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):159-163.
[75] Goodarzi M,Freitas M P.On the use of PLS and N-PLS in MIA-QSAR:Azole antifungals[J].Chemometrics and Intelligent Laboratory Systems,2009,96(1):59-62.
[76] Lee H W,Lee M W,Park J M.Multi-scale extension of PLS algorithm for advanced on-line process monitoring[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):201- 212.
[77] Nicola? B M,Theron K I,Lammertyn J.Kernel PLS regression on wavelet transformed NIR spectra for prediction of sugar content of apple[J].Chemometrics and Intelligent Laboratory Systems,2007,85(2):243-252.
[78] Preys S,Roger J M,Boulet J C.Robust calibration using orthogonal projection and experimental design.Application to the correction of the light scattering effect on turbid NIR spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,91(1):28-33.
[79] Tao S,Chen D,Zhao W.Fast pruning algorithm for multi-output LS-SVM and its application in chemical pattern classification[J].Chemometrics and Intelligent Laboratory Systems,2009,96(1):63-69.
[80] Xu L,Jiang J-H,Wu H-L,et al.Variable-weighted PLS[J].Chemometrics and Intelligent Laboratory Systems,2007,85(1):140-143.
[81] Yamamoto H,Yamaji H,Abe Y,et al.Dimensionality reduction for metabolome data using PCA , PLS , OPLS , and RFDA with differential penalties to latent varia- bles[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):136-142.
[82] Zhang L,Garcia-Munoz S.A comparison of different methods to estimate prediction uncertainty using Partial Least Squares (PLS):A practitioner's perspective[J].Chemome- trics and Intelligent Laboratory Systems,2009,97(2):152-158.
[83] Zhang Y,Zhang Y.Complex process monitoring using modified partial least squares method of independent component regression[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):143-148.
[84] Zhang Y.An improved QSPR study of standard formation enthalpies of acyclic alkanes based on artificial neural networks and genetic algorithm[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):162-172.
[85] Fei Q,Li M,Wang B,et al.Analysis of cefalexin with NIR spectrometry coupled to artificial neural networks with modified genetic algorithm for wavelength selec- tion[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):127-131.
[86] Zhang Y,Li H,Hou A,et al.Artificial neural networks based on principal component analysis input selection for quantification in overlapped capillary electrophoresis peaks[J].Chemome- trics and Intelligent Laboratory Systems,2006,82(1-2):165-175.
[87] Heise H M,Damm U,Kondepati V R.Reliable long-term continuous blood glucose monitoring for patients in critical care using micro-dialysis and infrared spectro- metry[J].Proc.of SPIE,2006,6093:31-39.
[88] Heise H M,Damm U,Bodenlenz M,et al.Bedside monitoring of subcutaneous interstitial glucose in healthy individuals using microdialysis and infrared spectrometry[J].Journal of Biomedical Optics,2007,12(2):024004.
[89] Saptari V,Youcef-Toumi K.Design of a mechanical-tunable filter spectrometer for noninvasive glucose measurement[J].Applied Optics,2004,43(13):2680- 2688.
[90] Saptari V,Youcef-Toumi K.Sensitivity analysis of near infrared glucose absorption signals:toward noninvasive blood glucose sensing[J].Proc.of SPIE,2000,4163:45-54.
[91] Chen J,Arnold M A,Small G W.Comparison of Combination and First Overtone Spectral Regions for Near-Infrared Calibration Models for Glucose and Other Biomolecules in Aqueous Solutions[J].Analytical Chemistry,2004,76(18):5405-5413.
[92] Amerov A K,Chen J,Arnold M A.Molar Absorptivities of Glucose and Other Biological Molecules in Aqueous Solutions over the First Overtone and Combination Regions of the Near-Infrared Spectrum[J].Applied Spectroscopy,2004,58(10):1195-1204.
[93] Olesberg J T,Arnold M A,Carmen Mermelstein.Tunable Laser Diode System for Noninvasive Blood Glucose Measurements[J].Applied Spectroscopy,2005,59(12): 1480-1484.
[94] Olesberg J T,Liu L Z,Zee V V,et al.In Vivo Near-Infrared Spectroscopy of Rat Skin Tissue with Varying Blood Glucose Levels[J].Analytical Chemistry,2006,78(1):215-223.
[95] Maruo K.New Methodology to Obtain a Calibration Model for Noninvasive Near- Infrared Blood Glucose Monitoring[J].Applied Spectroscopy,2006,60(4):441-449.
[96]陈华才,杨仲国,陈星旦,等.傅里叶变换近红外光谱法快速检测人血清生化成分[J].分析实验室,2005,24(7):17-20.
[97] Burmeister J J,Arnold M A.Evaluation of Measurement Sites for Noninvasive Blood Glucose Sending with Near-Infrared Transmission Spectroscopy[J].Clinical Chemistry, 1999,45(9):1621-1627.
[98] S?mann A . Non-invasive blood glucose monitoring by means of near infrared spectroscopy:investigation of long-term accuracy and stability[J].Exp Clin Endocrinol Diabetes,2000,108:406-413.
[99] Maruo K.Noninvasive Near-Infrared Blood Glucose Monitoring Using a Calibration Model Built by a Numerical Simulation Method:Trial Application to Patients in an Intensive Care Unit[J].Applied Spectroscopy,2006,60(12):1423-1431.
[100] Maruo K,Tsurugi M,Chen J,et al.Noninvasive blood glucose assay using a newly developed near-infrared system[J].IEEE,2003,9 (2) :322-330.
[101]陈文亮,崔厚欣,刘蓉,等.1100~1700nm近红外光谱无创血糖测量的OGTT实验研究[J].生物医学工程学杂志,2004,21(5):824-827.
[102]陈文亮,杨越,徐可欣,等.浮动基准法无创血糖浓度检测技术[J].纳米技术与精密工程,2007,5(4):298-301.
[103]刘蓉,徐可欣.近红外光谱无创血糖检测中体温变化的影响分析[J].天津大学学报2008,41(1):1-6.
[104]张洪艳,张来明,陈月,等.近红外漫反射光谱在人体血糖无创检测中的应用[J].激光与红外,2005,35(2):96-99.
[105] Hertzman A.Photoelectric plethysmography of the fingers and toes in man[J].Proc Soc Exp Biol Med,1937,37:529-534.
[106]青柳卓雄等.耳式血氧计的改良(日文)[C].第13回日本ME学会大会资料集,1974, 90-91.
[107] Mendelson Y.Pulse oximetry:Theory and applications for noninvasive monitoring [J].Clinical Chemistry,1992,38(9):1601-1607.
[108] Jeon K.Noninvasive total hemoglobin measurement[J].Journal of Biomedical Optics, 2002,7(1):45-50.
[109] Spigulis J.Optical noninvasive monitoring of skin blood pulsations [J].Applied Optics, 2005,44(10):1850-1857.
[110] Venckus G and Spigulis J.Frequency filtering effects on the single-period photoplethys- mography signals [J].Med Biol Eng Comput,1999,37(1):218-219.
[111] Nitzan M,Boer H,Turivnenko S,et al.Power spectrum analysis of spontaneous fluctuations in the photoplethysmographic signal [J].J Bas Clin Physiol Pharmacol ,1994,5(3),269-276.
[112] Nitzan M, Khanokh B, Slovik Y.The difference in pulse transit time to the toe and finger measured by photoplethysmography[J].Physiol. Meas. 2002,23:85-93.
[113] Yitzhak M,Burt D O.Non-invasive pulse oximetry utilizing skin reflectance photoplethys- mography[J].IEEE Trans Biomed Eng,1988,35:798-805.
[114] Joost P K,Lionel T,Christopher J G, et al.Reflectance pulseoximetry measurements from the retinal fundus[J].IEEE Trans Biomed Eng,1993,40:817-823.
[115] Edrich T,Flaig M,Knitza R,et al.Pulse oximetry:an improved in vitro model that reduces blood flowrelated artifacts[J].IEEE Trans Biomed Eng,2000,47(3):338-343.
[116]丁海泉,卢启鹏,王动民,等.近红外光谱无创血糖检测中有效信号提取方法的研究[J].光谱学与光谱分析,2010,30(1):50-53.
[117] Lou Z C,Zhang S,Yang Y M.Engineering Analysis for Pulse Wave and Its Application in Clinical Practice[M].Beijing:Science Press,2006:8-9,11-12,18-19,149.
[118]李顶立.基于脉搏波的无创连续血压测量方法研究[D].浙江大学博士学位论文,2008.
[119]姚建阁.基于脉搏波的动脉弹性指数算法研究和临床试验分析[D].重庆大学硕士学位论文,2008.
[120]董长虹,高志,余啸海.Matlab应用丛书-Matlab小波分析工具箱原理与应用[M].北京:国防工业出版社,2004:108-114.
[121]张樑．小波分析与分形方法在水电站振动信号处理中的应用研究[D].天津大学硕士学位论文,2005.
[122]吴桂芳,何勇.小波阈值降噪模型在红外光谱信号处理中的应用研究[J].光谱学与光谱分析,2009,29(12):3246-3249.
[123]温晓明.基于小波和小波包的脉搏波处理[J].重庆科技学院学报(自然科学版),2008,10(5):108-110.
[124]张坤,焦腾,付峰.运用小波模极大值滤波算法消除光电容积脉搏波中的运动干扰[J].仪器仪表学报,2009,30(3):586-589.
[125]王晨迪,汪丰.一种脉搏波小波降噪算法[J].中国体视学与图像分析,2009,14(1):99-105.
[126]杨琳,张松,杨益民,等.基于重搏波谷点的脉搏波波形特征量分析[J].北京生物医学工程,2008,27(3):229-233.
[127] Cameron B D,Gorde H W,Satheesan B,et al.The use of polarized laser light through the eye for noninvasive glucose monitoring[J].Diabetes Technol Ther,1999,1(2):135-140.
[128] Steeffs P G.Laser-based measurement of glucose in the ocular aqueous humor:An efficacious portal for determination of serum glucose levels[J].Dibaetes Technol Ther,1999,l:129-133.
[129] Borchert M S,Storrie-Lombardi M C,Lambert J L.A non-invasive glucose monitor: preliminary results in rabbits[J].Dibaetes Technol Ther,1999,1:145-150.
[130] Jagemann K,Fischbacher C,Danzer K,et al.Application of near-inrfared spectroscopy for non- invasive determination of blood/tissue glucose using neural networks[J].Zeitschrif fur Physikalische Chemie,1995,191:179-190.
[131] Robinson M R,Eaton R P,Haaland D M,et al.Noninvasive glucose monitoring in diabetic patients:a preliminary revaluation[J].Clin Chem,1992,38:1618-1622.
[132] Xu K X,Chen W L,Jiang J Y,et al.Study on optical measurement conditions for non- invasive blood glucose sensing[J].Proc SPIE,2004,5330:83-91.
[133]李庆波.近红外光谱分析中若干关键技术的研究[D].天津大学博士学位论文,2002:34-37,41-42.
[134]王焱,李刚,林凌,等.动态光谱检测中血液散射对等效光程长变化的影响[J].光谱学与光谱分析,2007,27(1):91-94.
[135]王燕,张松,杨益民,等.基于容积血流脉搏波的心血管血流参数监护模块的研制[J].北京生物医学工程,2006,25(2):148-151.
[136]刘静纨,陈建慧,罗志昌.人体微循环弹性腔模型与模型参数估计[J].北京生物医学工程,2001,20(2):102-105.
[137]罗志昌,张松,杨益民,等.微循环容积脉搏血流特征信息的研究[J].北京生物医学工程,2001,20(2):98-101.
[2]罗云瀚.近红外无创伤血糖浓度测量方法的组织光学基础及应用研究[D].天津大学博士学位论文,2006:3-7.
[3] Cote G L,Cameron B D.Noninvasive polarimertic measurement of glucose in cell culture media[J].J.Biomed.Opt.,1997,2(3):275-281.
[4] Cameron B D,Gorde H,Cote G L.Development of an optical polarimeter for in vivo glucose monitoring[C].Proc.SPIE,1999,3599:43-49.
[5] Berger A J,Koo T W,Itzkan I,et al.Multicomponent blood analysis by near-inrfared Raman spectroscopy[J].Appled Optics,1999,38(13):2916-2926.
[6] Kanger J S . Non-invasive detection of glucose using Raman spectroscopy[C] , Proc.SPIE,1999,3570:123-129.
[7] Larin K V,Motamedi M,Ashitkov T V.Specificity of noninvasive blood glucose sensing using optical coherence tomography technique:a pilot sutdy[J].Phys Med Biol,2003,48(10):1371- 90.
[8] Esenaliev R O,Larin K V,Larina I V.Noninvasive monitoring of glucose concentration with optical coherence tomography[J].Optics Letters,2001,26(13),992-994.
[9] Heise H M.Glucose Measurements by Vibrational Spectroscopy[M].Handbook of Vibrational Spectroscopy, Edited by John M.Chalmers.John Wiley&Sons,LTD,2002:3280-3294.
[10] Arnold M A,Small G W.Noninvasive Glucose Sensing[J].Analytical Chemistry,2005,77(17):5429-5439.
[11] Kim Y J,Hahn S,Yoon G.Detemrination of glucose in whole blood samples bymid-inrfared spectroscopy[J].Applied Optics,2003,42(4):745-749.
[12] Norris K.Possible medical applications of NIR[M].Making light work: Advances in near infrared spectroscopy,Edited by Murray I & Cowe I A.UK:Ian Michael Publication, 1992:596-602.
[13]刘蓉.近红外无创血糖测量一信号构成和拾取的理论及实验研究[D].天津大学博士学位论文,2006:2-3.
[14] Rosenthal R D.A portable non-invasive blood glucose meter[C].Oak-Ridge Conference,1993,312A:1244.
[15] Borchert M S,Storrie-Lombardi M C,Lambert J L.A non-invasive glucose monitor: preliminary results in rabbits[J].Diabetes Technology & Therapeutics,1999,l(2):145-151.
[16] Malin S F,Ruchti T L,Blank T B,et al.Non-invasive Prediction of glucose by near-infrared diffuse reflectance spectroscopy[J].Clinical Chemistry,1999,45:1651-1658.
[17] Peters,Richard K,Elmerick.Non-invasive glucose measuring device and method for measuring blood glucose,USP5,1999,910:109.
[18] Cingo N A,Small G W,Arnold M A,Determination of glucose in a synthetic biological matrix with decimated time-domain filtered near-inrfared inteerfrogram data[J].Vibrational Spectroscopy,2000,23:103-117.
[19] Marbach R,Heise H M.Optical Diffuse Reflectance Accessory for Measurements of Skin Tissue by Near-Infrared Spectroscopy[J],Applied Optics 1995,34:610-621.
[20] Gabriel Y I,Woznia K R,Mevorach M,et al.Transcutaneous glucose measurement using near-infrared spectroscopy during hypoglycemia[J].Diabetes Care,1999,22 (12):2026-2032.
[21] Maruo K,Tsurugi M,Tamura M.In Vivo Noninvasive Measurement of Blood Glucose by Near-Infrared Diffuse-Reflectance Spectroscopy[J].Applied Spectroscopy,2003,57(10):1236-1244.
[22]孙颖,杨展澜,吴瑾光,等.非损伤性血糖检测的研究进展[J].自然科学进展,2002,12(8):806-810.
[23]王炜,卞正中,张大龙.红外多波长无创人体血糖检测阵列模型的研究[J].生物医学工程学杂志,2003,20(4):716-719.
[24]王炜,卞正中,张大龙.红外无创血糖检测与阵列信号处理[J].红外技术,2003,25(2):60-64.
[25] Sun F,Kong D,Mei T,et al.Near infrared spectral methods for non-invasively measuring blood glucose,Proc.SPIE,2004,5281:595-601.
[26]林方,丁海曙,苏畅.Monte-Carlo方法研究生物组织内部光能分布[J].清华大学学报,2000,40(3):20-30.
[27]黄岚,丁海曙,王广志.用近红外漫反射光谱无损检测血糖的初步研究[J].光谱学与光谱分析,2002,22(3):357-391.
[28]沙宪政,李明菊.近红外光谱无创血糖检测技术的研究[J].医疗卫生装备,2003,24(6):29-31.
[29]李明菊,沙宪政.无创性血糖的光谱检测及临床研究状况[J].国外医学生物医学工程分册,2000,23(5):291-299.
[30]马显光,蒲晓允,陈仕国,等.无创血糖仪的研制[J].生物医学工程学杂志,2004,21(3):473-475.
[31] Yamakoshi K,Yamakoshi Y.Pulse glucometry:a new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophoto- metry[J].Journal of Biomedical Optics,2006,11(5):054028.
[32]李刚,李尚颖,林凌,等.基于动态光谱的脉搏血氧测量精度分析[J].光谱学与光谱分析,2006,26(10):1821-1824.
[33]刘蓉,徐可欣,陈文亮,等.光学无创血糖检测中的主要问题及研究进展[J].中国科学G辑:物理学力学天文学,2007,37(增刊):124-131.
[34]陈星旦.近红外光谱无创生化检验的可能性[J].光学精密工程,2008,16(5):759-763.
[35]陆婉珍.现代近红外光谱分析技术(第二版)(M).北京:中国石化出版社,2007:306-333.
[36]严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005.
[37] Williams P , Norris K . Near-Infrared technology in the agricultural and food industries[M], Second Edition, American Association of Cereal Chemists, Inc. 2001.
[38]丁海泉,卢启鹏,朴仁官,等.土壤有机质近红外光谱分析组合波长的优选[J].光学精密工程,2007,15(12):1946-1951.
[39]曹璞,潘涛,陈星旦.小型近红外玉米蛋白质成分分析仪器设计的波段选择[J].光学精密工程,2007,15(12):1952-1959.
[40]张军,陈星旦,朴仁官,等.用于食品成分分析的双探测器近红外光谱仪[J].光学精密工程,2008,16(6):986-992.
[41]陈华才,吕进,陈星旦,等.基于径向基函数网络的茶多酚总儿茶素近红外光谱检测模型的研究[J].光学精密工程,2006,14(1):58-62.
[42]赵强,张工力,陈星旦.多元散射校正对近红外光谱分析定标模型的影响[J].光学精密工程,2005,13(1):53-58.
[43]刘宏欣,张军,黄富荣,等.近红外光谱法快速测定啤酒的主要品质参数[J].光谱学与光谱分析,2008,28(2):313-316.
[44]罗云瀚,陈哲,陈星旦,等.近红外光谱无创血糖测量的极限检测浓度[J].光学精密工程,2008,16(5):784-788.
[45]张军,陈星旦,朴仁官,等.用于食品成分分析的双探测器近红外光谱仪[J].光学精密工程,2008,16(6):986-992.
[46]王动民,金尚忠,陈华才,等.棉-涤混纺面料中棉含量的近红外光谱分析[J].光学精密工程,2008,16(11):2051-2054.
[47]胡愉华,潘涛,陈星旦,等.甘蔗初压汁锤度近红外光谱分析的波段优选[J].光谱实验室,2009,26(1):90-95.
[48]梁家杰,潘涛,陈星旦,等.白砂糖色值近红外光谱分析的波段选择[J].红外技术,2009,31(2):90-94.
[49] Luo Y H,Huang F R,Li S P,et al.Detection limit of glucose concent ration with near-inf rared absorption and scattering spectroscopy[J].Chinese Physics Letters,2008,25 (3):1117-1119.
[50] Luo Y,Cui H,Gu X,et al.Determination of optimal source2detector separation in measuring chromophores in layered tissue with diffuse reflectance[J].Chinese Optics Letters,2005,3 (11):659-661.
[51]梁逸曾.白灰黑复杂多组份分析体系及其化学计量学算法[M].长沙:湖南科学技术出版社,1996:1-10.
[52]王惠文.偏最小二乘回归方法及其应用[M].北京:国防工业出版社,2000:28-110.
[53]柯以侃,董慧茹.分析化学手册第三分册-光谱分析[M].北京:化学工业出版社,1998:176- 177.
[54]罗运平,张军,郑仁富,等.正交信号校正在人体血糖近红外光谱分析中的研究[J].光谱实验室,2007,24(5):773-777.
[55]高荣强,范世福,严衍禄,等.近红外光谱的数据预处理研究[J].光谱学与光谱分析, 2004,12(24):1563-1565.
[56] Anzanello M J,Albin S L,Chaovalitwongse W A.Selecting the best variables for classifying production batches into two quality levels[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):111-117.
[57] Balabin R M,Safieva R Z,Lomakina E I.Wavelet neural network (WNN) approach for calibration model building based on gasoline near infrared (NIR) spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,93(1):58-62.
[58] Billeter J,Neuhold Y-M,Hungerbühler K.Kinetic hard-modelling and spectral validation of rank-deficient spectroscopic data:A case study[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):213-226.
[59] Cai W,Li Y,Shao X.A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,90(2):188-194.
[60] Cui W,Yan X.Adaptive weighted least square support vector machine regression integrated with outlier detection and its application in QSAR[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):130-135.
[61] Devos O,Ruckebusch C,Durand A,et al.Support vector machines (SVM) in near infrared(NIR)spectroscopy: Focus on parameters optimization and model interpret- tation[J].Chemometrics and Intelligent Laboratory Systems,2009,96(1):27-33.
[62] Fearn T, Riccioli C, Garrido-Varo A, et al . On the geometry of SNV and MSC[J].Chemome- trics and Intelligent Laboratory Systems,2009,96(1):22-26.
[63] Benoudjit N,Melgani F,Bouzgou H.Multiple regression systems for spectrophotometric data analysis[J].Chemometrics and Intelligent Laboratory Systems,2009,95(2):144-149.
[64] Bhatt N,Narasimhan S.Multivariate calibration of non-replicated measurements for the factored noise model[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2): 182-194.
[65] Gujral P,Amrhein M,Bonvin D,et al.Classification of magnetic resonance images from rabbit renal perfusion[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):173- 181.
[66] Huang Z,Tao W,Fang J,et al.Multivariate calibration of on-line enrichment near-infrared (NIR) spectra and determination of trace lead in water[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):195-200.
[67] Igne B,Roger J-M,Roussel S,et al.Improving the transfer of near infrared prediction models by orthogonal methods[J].Chemometrics and Intelligent Laboratory Systems,2009,99(1):57- 65.
[68] Kopriva I,Jeric I,Cichocki A.Blind decomposition of infrared spectra using flexible component analysis[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):170- 178.
[69] Liu X,Kruger U,Littler T,et al.Moving window kernel PCA for adaptive monitoring of nonlinear processes[J].Chemometrics and Intelligent Laboratory Systems,2009,96(2):132- 143.
[70] Liu X,Kruger U,Littler T,et al.Moving window kernel PCA for adaptive monitoring of nonlinear processes[J].Chemometrics and Intelligent Laboratory Systems,2009,96(2):132- 143.
[71] Janik L J,Forrester S T,Rawson A.The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis[J].Chemometrics and Intelligent Laboratory Systems,2009, 97(2):179-188.
[72] Kasemsumran S,Du Y P,Maruo K,et al.Improvement of partial least squares models for in vitro and in vivo glucose quantifications by using near-infrared spectroscopy andsearching combination moving window partial least squares[J].Chemometrics and Intelligent Laboratory Systems,2006,82(1-2):97-103.
[73]张玲.PLS定标法在近红外光谱分析仪中的应用研究[J].光学精密工程,2000,8 (3):238- 241.
[74] Kohonen J,Reinikainen S-P,Aaljoki K,et al.Non-linear PLS approach in score surface[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):159-163.
[75] Goodarzi M,Freitas M P.On the use of PLS and N-PLS in MIA-QSAR:Azole antifungals[J].Chemometrics and Intelligent Laboratory Systems,2009,96(1):59-62.
[76] Lee H W,Lee M W,Park J M.Multi-scale extension of PLS algorithm for advanced on-line process monitoring[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):201- 212.
[77] Nicola? B M,Theron K I,Lammertyn J.Kernel PLS regression on wavelet transformed NIR spectra for prediction of sugar content of apple[J].Chemometrics and Intelligent Laboratory Systems,2007,85(2):243-252.
[78] Preys S,Roger J M,Boulet J C.Robust calibration using orthogonal projection and experimental design.Application to the correction of the light scattering effect on turbid NIR spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,91(1):28-33.
[79] Tao S,Chen D,Zhao W.Fast pruning algorithm for multi-output LS-SVM and its application in chemical pattern classification[J].Chemometrics and Intelligent Laboratory Systems,2009,96(1):63-69.
[80] Xu L,Jiang J-H,Wu H-L,et al.Variable-weighted PLS[J].Chemometrics and Intelligent Laboratory Systems,2007,85(1):140-143.
[81] Yamamoto H,Yamaji H,Abe Y,et al.Dimensionality reduction for metabolome data using PCA , PLS , OPLS , and RFDA with differential penalties to latent varia- bles[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):136-142.
[82] Zhang L,Garcia-Munoz S.A comparison of different methods to estimate prediction uncertainty using Partial Least Squares (PLS):A practitioner's perspective[J].Chemome- trics and Intelligent Laboratory Systems,2009,97(2):152-158.
[83] Zhang Y,Zhang Y.Complex process monitoring using modified partial least squares method of independent component regression[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):143-148.
[84] Zhang Y.An improved QSPR study of standard formation enthalpies of acyclic alkanes based on artificial neural networks and genetic algorithm[J].Chemometrics and Intelligent Laboratory Systems,2009,98(2):162-172.
[85] Fei Q,Li M,Wang B,et al.Analysis of cefalexin with NIR spectrometry coupled to artificial neural networks with modified genetic algorithm for wavelength selec- tion[J].Chemometrics and Intelligent Laboratory Systems,2009,97(2):127-131.
[86] Zhang Y,Li H,Hou A,et al.Artificial neural networks based on principal component analysis input selection for quantification in overlapped capillary electrophoresis peaks[J].Chemome- trics and Intelligent Laboratory Systems,2006,82(1-2):165-175.
[87] Heise H M,Damm U,Kondepati V R.Reliable long-term continuous blood glucose monitoring for patients in critical care using micro-dialysis and infrared spectro- metry[J].Proc.of SPIE,2006,6093:31-39.
[88] Heise H M,Damm U,Bodenlenz M,et al.Bedside monitoring of subcutaneous interstitial glucose in healthy individuals using microdialysis and infrared spectrometry[J].Journal of Biomedical Optics,2007,12(2):024004.
[89] Saptari V,Youcef-Toumi K.Design of a mechanical-tunable filter spectrometer for noninvasive glucose measurement[J].Applied Optics,2004,43(13):2680- 2688.
[90] Saptari V,Youcef-Toumi K.Sensitivity analysis of near infrared glucose absorption signals:toward noninvasive blood glucose sensing[J].Proc.of SPIE,2000,4163:45-54.
[91] Chen J,Arnold M A,Small G W.Comparison of Combination and First Overtone Spectral Regions for Near-Infrared Calibration Models for Glucose and Other Biomolecules in Aqueous Solutions[J].Analytical Chemistry,2004,76(18):5405-5413.
[92] Amerov A K,Chen J,Arnold M A.Molar Absorptivities of Glucose and Other Biological Molecules in Aqueous Solutions over the First Overtone and Combination Regions of the Near-Infrared Spectrum[J].Applied Spectroscopy,2004,58(10):1195-1204.
[93] Olesberg J T,Arnold M A,Carmen Mermelstein.Tunable Laser Diode System for Noninvasive Blood Glucose Measurements[J].Applied Spectroscopy,2005,59(12): 1480-1484.
[94] Olesberg J T,Liu L Z,Zee V V,et al.In Vivo Near-Infrared Spectroscopy of Rat Skin Tissue with Varying Blood Glucose Levels[J].Analytical Chemistry,2006,78(1):215-223.
[95] Maruo K.New Methodology to Obtain a Calibration Model for Noninvasive Near- Infrared Blood Glucose Monitoring[J].Applied Spectroscopy,2006,60(4):441-449.
[96]陈华才,杨仲国,陈星旦,等.傅里叶变换近红外光谱法快速检测人血清生化成分[J].分析实验室,2005,24(7):17-20.
[97] Burmeister J J,Arnold M A.Evaluation of Measurement Sites for Noninvasive Blood Glucose Sending with Near-Infrared Transmission Spectroscopy[J].Clinical Chemistry, 1999,45(9):1621-1627.
[98] S?mann A . Non-invasive blood glucose monitoring by means of near infrared spectroscopy:investigation of long-term accuracy and stability[J].Exp Clin Endocrinol Diabetes,2000,108:406-413.
[99] Maruo K.Noninvasive Near-Infrared Blood Glucose Monitoring Using a Calibration Model Built by a Numerical Simulation Method:Trial Application to Patients in an Intensive Care Unit[J].Applied Spectroscopy,2006,60(12):1423-1431.
[100] Maruo K,Tsurugi M,Chen J,et al.Noninvasive blood glucose assay using a newly developed near-infrared system[J].IEEE,2003,9 (2) :322-330.
[101]陈文亮,崔厚欣,刘蓉,等.1100~1700nm近红外光谱无创血糖测量的OGTT实验研究[J].生物医学工程学杂志,2004,21(5):824-827.
[102]陈文亮,杨越,徐可欣,等.浮动基准法无创血糖浓度检测技术[J].纳米技术与精密工程,2007,5(4):298-301.
[103]刘蓉,徐可欣.近红外光谱无创血糖检测中体温变化的影响分析[J].天津大学学报2008,41(1):1-6.
[104]张洪艳,张来明,陈月,等.近红外漫反射光谱在人体血糖无创检测中的应用[J].激光与红外,2005,35(2):96-99.
[105] Hertzman A.Photoelectric plethysmography of the fingers and toes in man[J].Proc Soc Exp Biol Med,1937,37:529-534.
[106]青柳卓雄等.耳式血氧计的改良(日文)[C].第13回日本ME学会大会资料集,1974, 90-91.
[107] Mendelson Y.Pulse oximetry:Theory and applications for noninvasive monitoring [J].Clinical Chemistry,1992,38(9):1601-1607.
[108] Jeon K.Noninvasive total hemoglobin measurement[J].Journal of Biomedical Optics, 2002,7(1):45-50.
[109] Spigulis J.Optical noninvasive monitoring of skin blood pulsations [J].Applied Optics, 2005,44(10):1850-1857.
[110] Venckus G and Spigulis J.Frequency filtering effects on the single-period photoplethys- mography signals [J].Med Biol Eng Comput,1999,37(1):218-219.
[111] Nitzan M,Boer H,Turivnenko S,et al.Power spectrum analysis of spontaneous fluctuations in the photoplethysmographic signal [J].J Bas Clin Physiol Pharmacol ,1994,5(3),269-276.
[112] Nitzan M, Khanokh B, Slovik Y.The difference in pulse transit time to the toe and finger measured by photoplethysmography[J].Physiol. Meas. 2002,23:85-93.
[113] Yitzhak M,Burt D O.Non-invasive pulse oximetry utilizing skin reflectance photoplethys- mography[J].IEEE Trans Biomed Eng,1988,35:798-805.
[114] Joost P K,Lionel T,Christopher J G, et al.Reflectance pulseoximetry measurements from the retinal fundus[J].IEEE Trans Biomed Eng,1993,40:817-823.
[115] Edrich T,Flaig M,Knitza R,et al.Pulse oximetry:an improved in vitro model that reduces blood flowrelated artifacts[J].IEEE Trans Biomed Eng,2000,47(3):338-343.
[116]丁海泉,卢启鹏,王动民,等.近红外光谱无创血糖检测中有效信号提取方法的研究[J].光谱学与光谱分析,2010,30(1):50-53.
[117] Lou Z C,Zhang S,Yang Y M.Engineering Analysis for Pulse Wave and Its Application in Clinical Practice[M].Beijing:Science Press,2006:8-9,11-12,18-19,149.
[118]李顶立.基于脉搏波的无创连续血压测量方法研究[D].浙江大学博士学位论文,2008.
[119]姚建阁.基于脉搏波的动脉弹性指数算法研究和临床试验分析[D].重庆大学硕士学位论文,2008.
[120]董长虹,高志,余啸海.Matlab应用丛书-Matlab小波分析工具箱原理与应用[M].北京:国防工业出版社,2004:108-114.
[121]张樑．小波分析与分形方法在水电站振动信号处理中的应用研究[D].天津大学硕士学位论文,2005.
[122]吴桂芳,何勇.小波阈值降噪模型在红外光谱信号处理中的应用研究[J].光谱学与光谱分析,2009,29(12):3246-3249.
[123]温晓明.基于小波和小波包的脉搏波处理[J].重庆科技学院学报(自然科学版),2008,10(5):108-110.
[124]张坤,焦腾,付峰.运用小波模极大值滤波算法消除光电容积脉搏波中的运动干扰[J].仪器仪表学报,2009,30(3):586-589.
[125]王晨迪,汪丰.一种脉搏波小波降噪算法[J].中国体视学与图像分析,2009,14(1):99-105.
[126]杨琳,张松,杨益民,等.基于重搏波谷点的脉搏波波形特征量分析[J].北京生物医学工程,2008,27(3):229-233.
[127] Cameron B D,Gorde H W,Satheesan B,et al.The use of polarized laser light through the eye for noninvasive glucose monitoring[J].Diabetes Technol Ther,1999,1(2):135-140.
[128] Steeffs P G.Laser-based measurement of glucose in the ocular aqueous humor:An efficacious portal for determination of serum glucose levels[J].Dibaetes Technol Ther,1999,l:129-133.
[129] Borchert M S,Storrie-Lombardi M C,Lambert J L.A non-invasive glucose monitor: preliminary results in rabbits[J].Dibaetes Technol Ther,1999,1:145-150.
[130] Jagemann K,Fischbacher C,Danzer K,et al.Application of near-inrfared spectroscopy for non- invasive determination of blood/tissue glucose using neural networks[J].Zeitschrif fur Physikalische Chemie,1995,191:179-190.
[131] Robinson M R,Eaton R P,Haaland D M,et al.Noninvasive glucose monitoring in diabetic patients:a preliminary revaluation[J].Clin Chem,1992,38:1618-1622.
[132] Xu K X,Chen W L,Jiang J Y,et al.Study on optical measurement conditions for non- invasive blood glucose sensing[J].Proc SPIE,2004,5330:83-91.
[133]李庆波.近红外光谱分析中若干关键技术的研究[D].天津大学博士学位论文,2002:34-37,41-42.
[134]王焱,李刚,林凌,等.动态光谱检测中血液散射对等效光程长变化的影响[J].光谱学与光谱分析,2007,27(1):91-94.
[135]王燕,张松,杨益民,等.基于容积血流脉搏波的心血管血流参数监护模块的研制[J].北京生物医学工程,2006,25(2):148-151.
[136]刘静纨,陈建慧,罗志昌.人体微循环弹性腔模型与模型参数估计[J].北京生物医学工程,2001,20(2):102-105.
[137]罗志昌,张松,杨益民,等.微循环容积脉搏血流特征信息的研究[J].北京生物医学工程,2001,20(2):98-101.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |