Advanced Statistical Techniques for Noninvasive Hyperglycemic States Detection in Mice Using Millimeter-Wave Spectroscopy

Abstract

In this article, we discuss the use of advanced statistical techniques (functional data analysis) in millimeter-wave (mm-wave) spectroscopy for biomedical applications. We employ a W-band transmit-receive unit with reference channel to acquire the spectral data. The choice of the W-band is based on a trade-off between penetration through the skin providing an upper bound for the frequencies and spectral content across the band. The data obtained are processed using Functional Principal Component Logit Regression (FPCLoR), which enables to obtain a predictive model for sustained hyperglycemia, typically associated with diabetes. The predictions are based on the transmission data from non-invasive mm-wave spectrometer at W-band. We show that there exists a frequency range most suitable for identification, classification, and prediction of sustained hyperglycemia when evaluating the functional parameter of the FPCLoR model (β). This allows for the optimization of the spectroscopic instrument in the aim to obtain a compact and potential low-cost non-invasive instrument for hyperglycemia assessment. Furthermore, we also demonstrate that the statistical tools alleviate the problem of calibration, which is a serious obstacle in similar measurements at terahertz and IR frequencies.

Hyperspectral terahertz imaging with electro-optic dual combs and a FET-based detector

“…The main limitation of the current system is evidently the long time needed for the acquisition of the hypercube; nevertheless, recent dual-comb developments promise to overcome current technological challenges to consistently shrink acquisition times to a single second in the next few years 37 , 38 . Besides this, we plan to incorporate spectral processing and classification to the next versions of the system for the identification and quantification of analytes with distinctive absorption spectrum 39 .…”

Integrated Millimeter-Wave and Terahertz Analyzers for Biomedical Applications

“…In [4], a microfluidics-based sensor solution for enhanced cancer cell detection through the use of wideband microwave spectroscopy of single biological cells has been proposed [5]- [7]. In addition, various research on the noninvasive sensing of glucose levels has been performed [8]- [12]. Furthermore, different promising tissue diagnostics [13], including hydration monitoring [14] and cancer identification [15], exist.…”