Prediction of Aqueous Glucose Concentration Using Hyperspectral Imaging

Near infrared hyperspectral imaging (HSI) is an emerging optical imaging modality which boasts several advantages. Compared to conventional spectroscopy, HSI pro-vides thousands of spectral samples with embedded spatial information in a single image. This allows the collection of high quality and high volume spectral signals in a short time. In this paper, transmissive HSI combined with Partial Least Squares Regression (PLSR) was used to non-invasively predict aqueous glucose concentration. Aqueous glucose samples are prepared with concentration ranging from 0 - 1000 mg/dL at intervals of 100 mg/dL and 100 - 300 mg/dL at intervals of 20 mg/dL. Our results are validated using leave-one-concentration-out cross validation, and demonstrate the feasibility of the proposed aqueous glucose concentration detection method using the combination of HSI and PLSR.