基于能量守恒与光谱法的无创血糖检测技术

Noninvasive Detection of Blood Glucose Based on Conservation of Energy Metabolism and Spectroscopy

摘要:

传统的人体血糖检测方法是有创的,具有一定的局限性。文章提出一种结合能量守恒法与光谱法的血糖检测技术,该技术能够实现人体血糖的无创、实时和准确检测。首先设计了一种人体体征数据采集装置,用于实时采集血糖相关数据并上传至上位机。然后将数据分别用多元线性回归、k近邻回归和支持向量回归三种机器学习算法进行分析评估,对比得出最优算法用于无创血糖检测。实验证明,提出的无创血糖检测技术是可行的,其中基于支持向量回归算法的测量准确度最高,相关系数高达0.862,具有较高的准确性和鲁棒性。

Abstract:

Traditional human blood glucose testing methods are invasive and have certain limitations. In this paper, a new technique is proposed by combining energy conservation method and spectroscopy to realize non-invasive, real-time and accurate detection of human blood glucose. Firstly, a body sign data collection device was designed to collect blood glucose-related data in real time and upload it to the upper computer. Then the data were analyzed and evaluated with such three different machine learning algorithms as multiple linear regressions, k-nearest neighbor regression and support vector regression, thus the optimal algorithm for non-invasive blood glucose detection could be confirmed by comparisons. Experimental results show that, the proposed technique for noninvasive blood glucose detection realizes high feasibility, accuracy and robustness, the measurement accuracy based on the support vector regression algorithm is the best, and the correlation coefficient reached as high as 0.862.