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 provides 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.