Noninvasive Glucose Measurements in Tissue Simulating Phantoms Using a Solid-State Near-Infrared Sensor

Area of Science:

• Biomedical Optics
• Spectroscopy
• Medical Devices

Background:

• Noninvasive glucose monitoring is crucial for diabetes management.
• Near-infrared (NIR) spectroscopy offers a promising avenue for noninvasive measurements.
• Developing robust and accurate NIR spectrometers is an ongoing challenge.

Purpose of the Study:

• To benchmark the performance of a novel solid-state laser-based NIR spectrometer.
• To compare its analytical utility against a Fourier-transform (FT) spectrometer for glucose measurements.
• To assess the feasibility of the laser platform for noninvasive human skin measurements.

Main Methods:

• Aqueous phantoms mimicking human skin composition were used for calibration and testing.
• Spectroscopic performance was evaluated by analyzing 100% lines and root mean square (RMS) noise levels.
• Partial least squares (PLS) regression was employed to assess analytical utility for glucose quantification.

Main Results:

• The solid-state laser spectrometer exhibited a median RMS noise level of 667.2 µAU, compared to 327.8 µAU for the FT spectrometer.
• A PLS model using laser data achieved a standard error of cross-validation (SECV) of 7.82 mg/dL over 1401-2238 nm.
• The laser platform's SECV was comparable to the FT spectrometer's SECV of 6.62 mg/dL (1551-2378 nm), with the difference attributed to higher spectral noise.

Conclusions:

• The solid-state laser spectrometer demonstrates significant analytical utility for noninvasive glucose monitoring.
• Its performance is competitive with established FT spectrometers, indicating potential for clinical applications.
• Further optimization to reduce spectral noise could enhance the laser platform's accuracy and selectivity.