Suppr超能文献

化学计量学方法用于改进基于 VCSEL 的葡萄糖预测。

Chemometric approach for improving VCSEL-based glucose predictions.

机构信息

Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.

出版信息

IEEE Trans Biomed Eng. 2010 Mar;57(3):578-85. doi: 10.1109/TBME.2009.2032160. Epub 2009 Sep 25.

Abstract

Optical methods are one of the painless and promising techniques that can be used for blood glucose predictions for diabetes patients. The use of thermally tunable vertical cavity surface-emitting lasers (VCSELs) as the light source to obtain blood absorption spectra, along with the multivariate technique partial least squares for analysis and glucose estimation, has been demonstrated. With further improvements by using data preprocessing and two VCSELs, we have achieved a clinically acceptable level in the physiological range in buffered solutions. The results of previous experiments conducted using white light showed that increasing the number of wavelength intervals used in the analysis improves the accuracy of prediction. The average prediction error, using absorption spectra from one VCSEL in aqueous solution, is about 1.2 mM. This error is reduced to 0.8 mM using absorption spectra from two VCSELs. This result confirms that increasing the number of VCSELs improves the accuracy of prediction.

摘要

光学方法是一种无痛且有前途的技术,可用于预测糖尿病患者的血糖水平。已经证明,可以使用热可调谐垂直腔面发射激光器 (VCSEL) 作为光源来获得血液吸收光谱,并结合多元技术偏最小二乘法进行分析和葡萄糖估计。通过使用数据预处理和两个 VCSEL 进一步改进,我们已经在生理范围内的缓冲溶液中达到了临床可接受的水平。以前使用白光进行的实验结果表明,增加分析中使用的波长间隔数量可以提高预测的准确性。使用水溶液中的一个 VCSEL 的吸收光谱,平均预测误差约为 1.2mM。使用两个 VCSEL 的吸收光谱,将误差降低到 0.8mM。这一结果证实,增加 VCSEL 的数量可以提高预测的准确性。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验