Author(s)

Bo Zeng, Wei Wang, Na Wang, Funing Li, Fulong Zhai, Lintao Hu

School of Information Science and Engineering, Lanzhou University, Lanzhou, China.

In this research, a near infrared multi-wavelength noninvasive blood glucose monitoring system with distributed laser multi-sensors is applied to monitor human blood glucose concentration. In order to improve the monitoring accuracy, a multi-sensors information fusion model based on Back Propagation Artificial Neural Network is proposed. The Root- Mean-Square Error of Prediction for noninvasive blood glucose measurement is 0.088mmol/L, and the correlation coefficient is 0.94. The noninvasive blood glucose monitoring system based on distributed multi-sensors information fusion of multi-wavelength NIR is proved to be of great efficient. And the new proposed idea of measurement based on distri- buted multi-sensors, shows better prediction accuracy.

Noninvasive Glucose Monitoring; NIR Arrays Signals Fusion; BP-Artificial Neural Network

Zeng, B. , Wang, W. , Wang, N. , Li, F. , Zhai, F. and Hu, L. (2013) Noninvasive Blood Glucose Monitoring System Based on Distributed Multi-Sensors Information Fusion of Multi-Wavelength NIR. Engineering, 5, 553-560. doi: 10.4236/eng.2013.510B114.