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Non-invasive optical glucose detection faces significant challenges due to the need to identify and extract glucose-induced signals amidst continuous human variations and probing disturbances. To ensure stable near-infrared optical signal acquisition in vivo, we enhanced the design of a wearable detector and introduced strategies to mitigate human-induced variations, aiming to minimize unnecessary fluctuations and interferences. Our custom-designed multi-ring InGaAs detector, combined with a differential method, achieved a high signal-to-noise ratio (SNR) during in vivo data acquisition. The proposed posture-aiming method enabled continuous, high-stability data collection for 1-2 hours in vivo, even with slight human motion. These enhancements enable the direct acquisition of near-infrared optical signals modulated by blood glucose levels in vivo. Results from Monte Carlo (MC) simulations and data collected from fasting subjects validated the detection approaches’ capability for stable spectroscopic detection. We conducted 30 oral glucose tolerance tests (OGTT) involving 28 volunteers. At 1550 nm, we successfully extracted optical signals that were continuously synchronized with blood glucose fluctuations, achieving an average coefficient of determination (R2) of 0.82 across the 30 OGTT tests.
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