Abstract
Real-time blood glucose detection is an essential tool for diabetes monitoring. Non-invasive blood glucose detection technology is one of the current research hotspots in this field. Previous research mainly focused on improving the system's detection capability to obtain signals with low signal-to-noise ratio and high quality, and simple methods are often used in signal processing. Moreover, photoacoustic signal simulation also simplifies the influence of the transmission medium on the signal. In the present study, we built a new simulation model which considers human skin, blood, and the detector's limitations, to obtain a more practical photoacoustic signal. We then proposed a blood glucose detection algorithm based on Teager-Kaiser main energy (TKME) to overcome noise and medium interference and achieve a high detection accuracy at low SNR. Finally, the simulation and actual data were utilised during the experiment, and the detection error was 15 mg/dL (SNR = 10 dB).
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