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標題: 近紅外線光譜法應用於無創性血糖量測之可行性評估
Evaluation of the non-invasive blood glucose measurement by using NIR spectroscopy
作者: 張雯琳
Chang, Wen-Lin
關鍵字: near-infrared spectroscopy
blood sugar
aqueous solution
partial least squares regression
出版社: 生物產業機電工程學系所
引用: [1]. 王盈錦等。2002。材料的表面性質。出自”生物醫學材料”。初版,145-146。蔡瑞瑩。台北:合計圖書。 [2]. 林友明。2002。碩士論文。以NIR光譜分析檢測米象蟲污染之研究。台中:中興大學生物產業機電工程學系。 [3]. 周劍文。2008。SMBG自我血糖監測。中華民國糖尿病衛教學會,2008年12月會訊。 [4]. 陶婉珍。2007。現代近紅外光譜分析技術。第二版。中國石化出版社。 [5]. 劉建學。2008。實用近紅外光譜分析技術。第一版。北京:科學出版社。 [6]. 嚴衍祿等。2005。近紅外光譜分析基礎與應用。第一版。中國輕工業出版社。 [7]. 工研院經資中心。糖尿病醫療市場發展現況與趨勢。血糖監測技術發展與產品趨勢。網址:。上網日期2008-11-06。 [8]. 陳加忠。2000。近紅外線之應用原理與其限制。台中:中興大學生機系生物系統工程研究室。 [9]. Cen H. and Y. He. 2007. Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science & Technology 18(2007):72-83. [10]. Ferrante do Amaral C.E., B. Wolf. 2008. Current development in non-invasive glucose monitoring. Medical Engineering & Physics 30(2008):541-549. [11]. Haaland D. M., M. R. Robinson, G. W. Koepp, E. V. Thomas, and R. P. Eaton. 1992. Reagentless Near-Infrared Determination of Glucose in Whole Blood Using Multivariate Calibration. Applied Spectroscopy. 46(10):1575-1578. [12]. Malin S. F., T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre. 1999. Noninvasive Prediction of Glucose by Near-Infrared Diffuse Reflectance Spectroscopy. Clinical Chemistry 45:9, 1651-1658. [13]. Myers, Raymond M.. 2000. Classical and Modern Regression with Applications. 2nd ed. Pacific Grove, CA: Duxbury. [14]. Næs T., T. Isaksson, T. Fearn, and T. Davies. 2002. A User-Friendly Guide to Multivariate Calibration and Classification. NIR Publications. [15]. Ott R.L. and M. Longnecker. 2001. An Introduction to Statistical Methods and Data Analysis. 5th ed. Pacific Grove, CA: Duxbury. [16]. Pasquini C.. 2003. Near Infrared Spectroscopy: Fundamentals, Practical Aspects and Analytical Applications. J. Braz. Chem. Soc. 14(2):198-219. [17]. Robinson M.R., R. P. Eaton, D. M. Haaland, G. W. Koepp, E. V. Thomas, B. R. Stallard, and P. L. Robinson. 1992. Noninvasive glucose monitoring in diabetic patients: a preliminary evaluation. Clin. Chem. 38/9, 1618-1622. [18]. Tura A., A. Maran, and Giovanni Pacini. 2007. Non-invasive glucose monitoring: Assessment of technologies and devices according to quantitative criteria. Diabetes Research and Clinical Practice 77(2007):16-40. [19]. Wold S., M. Sjöström, L. Eriksson. 2001. PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems 58(2001):109-130.
摘要: 近年來,近紅外線(NIR)光譜法是一種非破壞、非侵入式且可以快速量測的量測技術,被廣泛應用於食品科學、醫學等領域。目前糖尿病患者所使用的血糖計多為針刺手指取血的侵入式量測,帶給病患諸多不便與痛苦,更帶來感染的危險,所以利用近紅外線光譜法的特性發展非侵入式的血糖量測技術。 本研究目的在於探討本實驗儀器在僅以水當基質的情況下,量測不同濃度的葡萄糖水溶液,探討其光譜的差異性,說明本實驗儀器所能量測的葡萄糖濃度之解析能力。並使用偏最小平方迴歸方法建模,討論模型的預測能力來評估本實驗儀器應用於血糖量測之可行性。 研究結果發現,本實驗儀器對不同濃度之葡萄糖水溶液具有分辨能力,但由於其量測結果的組內變異大於組間變異,重現性不佳。模型的預測能力無法滿足美國食品與藥物管理局(FDA)的要求。
Near-infrared spectroscopy is a non-destruction, non-invasive and rapid technique, it has been applied widely in food science, medicine and so on in recent years. At present, the diabetic almost use the invasion type of finger-stick method to measure blood glucose, takes inconvenience, pain and danger to infection. Therefore, the apply of the near-infrared spectroscopy to develop the non-invasion blood glucose measurement technology is very important. The purpose of this study is to measure the glucose aqueous solutions at different concentration and to discuss whether the spectra could be compared or not to interpret the resolution of the instrument. The non-invasive blood glucose measurement by using the experiment instrument is to be evaluated by using partial least squares regression to construct the models and discuss their prediction ability. The results indicated the instrument could be used to compare the spectra of glucose aqueous solutions at different concentration. However, the variance within groups larger than the variance between groups, then resulted in poor reproduction. The prediction of the models is not good enough to satisfy the request of American Food and Drug Administration (FDA).
其他識別: U0005-0208200916593000
Appears in Collections:生物產業機電工程學系



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