Uwadaira Yasuhiro, Ikehata Akifumi, Momose Akiko, Miura Masayo
Analytical Science Division, Food Research Institute, NARO, 2-1-12 Kannondai, Tsukuba 305-8642, Japan.
Food and Cookery Sciences, Kagawa Nutrition University, 3-9-21 Chiyoda, Sakado 350-0288, Japan.
Biomed Opt Express. 2016 Jun 21;7(7):2729-37. doi: 10.1364/BOE.7.002729. eCollection 2016 Jul 1.
The "glucose-linked wavelength" in the short-wavelength near-infrared (NIR) region, in which the light intensity reflected from the hand palm exhibits a good correlation to the blood glucose value, was investigated. We performed 391 2-h carbohydrate tolerance tests (CTTs) using 34 participants and a glucose-linked wavelength was successfully observed in almost every CTT; however, this wavelength varied between CTTs even for the same person. The large resulting data set revealed the distribution of the informative wavelength. The blood glucose values were efficiently estimated by a simple linear regression with clinically acceptable accuracies. The result suggested the potential for constructing a personalized low-invasive blood glucose sensor using short-wavelength NIR spectroscopy.
研究了短波长近红外（NIR）区域中的“葡萄糖关联波长”，在此区域中，从手掌反射的光强度与血糖值呈现出良好的相关性。我们对34名参与者进行了391次2小时的碳水化合物耐量试验（CTT），并且几乎在每次CTT中都成功观测到了葡萄糖关联波长；然而，即使对于同一个人，该波长在不同的CTT之间也会有所变化。由此产生的大量数据集揭示了信息波长的分布情况。通过简单的线性回归能够以临床可接受的准确度有效地估算出血糖值。该结果表明了利用短波长NIR光谱法构建个性化低侵入性血糖传感器的潜力。
