Cloud Computing-Based Non-Invasive Glucose Monitoring for Diabetic Care

Near infrared photoacoustic spectroscopy is utilized for the development of a continuous non-invasive glucose monitoring system for diabetics. A portable embedded system for taking photoacoustic measurements on tissues to estimate glucose concentration is implemented using field programmable gate array (FPGA). The back-end architecture for high-speed data acquisition and de-noising of photoacoustic measurements operates at 274.823 MHz on a Xilinx Virtex-II Pro FPGA. The glucose measurement technique is verified in vitro on glucose solutions and in vivo on tissues, with photoacoustic signal amplitude varying linearly with sample glucose concentration. A kernel-based regression algorithm using multiple features of the photoacoustic signal is used to estimate glucose concentration from photoacoustic measurements. The calibration algorithm provides a superior performance over previous efforts with a mean absolute relative difference of 8.84% and Clarke Error Grid distribution of 92.86% and 7.14% over Zones A and B of the grid. A cloud computing platform for automated monitoring of blood glucose levels is proposed to enable individuals with diabetes to connect with doctors and caretakers. The developed system is connected to the cloud service using a mobile device, which facilitates implementation of computationally intensive calibration tasks and the storage and analysis of measurement data for treatment and monitoring.