| dc.description.abstract | The World Health Organization published a journal in 2016 pointing out that the global population of diabetes continues to rise and that diabetes is ranked fifth in the country′s mortality rate. This shows that regular blood glucose monitoring is very important, but conventional blood glucose machines cannot measure continuously, and blood collection process causes discomfort to the user. Therefore, in recent years, the development of blood glucose machines has gradually been directed towards non-invasive blood glucose measurement. Among the currently proposed technologies, optical measurement methods are most promising. However, in terms of development, because the glucose signal is rather weak, it is easy to be subject to external factors to interfere with the error during optical measurement. Many of the light sources used in the research are near-infrared light. Therefore, baseline drift that is susceptible to temperature is also found during measurement. Therefore, this study intends to develop a non-invasive blood glucose detection system using dual-lamp measurement technology. The system uses a single-chip microcomputer Arm-Cortex M4 to communicate and connect AFE4490 Chip with the SPI method and to use the PPG measurement probe designed by the laboratory with H-bridge circuit for dual light source PPG data read, PPG signal data sampling rate is set to 500Hz, and then use the Bluetooth method to test the PPG data back to the computer and then use matlab to calculate algorithm.
The system uses near-red light sensitivity to blood glucose as the light source used by the system, and uses green light as the calibration reference to eliminate measurement errors caused by sympathetic nerve changes. The green light and near-infrared light PPG signals of 18 normal healthy people were measured, and the blood glucose level of subjects was changed by taking sugar water, and blood glucose was measured with the commercially available blood glucose meter OneTouch-UltraEasy, and then verified by regression analysis. The error of the blood glucose variation predicted by the system and the actual measurement was 22.57%, confirming the feasibility of the optical blood glucose detection technology. However, in this study, it was found that the values calculated by the algorithm due to differences in the individual′s physiological conditions may have a problem of baseline differences among the subjects. Therefore, the results presented in this system are all the changes in the blood glucose level with Optical activity changes,form this reason our system for the measurement of blood glucose values still need to be recalibrated for individual statment and that can be applied to blood glucose measurement. | en_US |