Next Article in Journal
Computed Tomography (CT) Image Quality Enhancement via a Uniform Framework Integrating Noise Estimation and Super-Resolution Networks
Next Article in Special Issue
3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology
Previous Article in Journal
Measurement Method Based on Multispectral Three-Dimensional Imaging for the Chlorophyll Contents of Greenhouse Tomato Plants
Previous Article in Special Issue
Software-Defined Doppler Radar Sensor for Human Breathing Detection
Open AccessArticle

Early, Non-Invasive Sensing of Sustained Hyperglycemia in Mice Using Millimeter-Wave Spectroscopy

1
Department of Electronic Technology, Universidad Carlos III de Madrid, Leganes, 28911 Madrid, Spain
2
Instituto de Investigaciones sanitarias de la Fundación Jiménez Díaz (IIS-FJD), 28040 Madrid, Spain
3
Department of Statistics, Universidad Carlos III de Madrid, Leganes, 28911 Madrid, Spain
4
Santander Big Data Institute, Universidad Carlos III de Madrid, Getafe, 28903 Madrid, Spain
5
Physics Institute, Goethe University Frankfurt am Main, 60438 Frankfurt am Main, Germany
6
Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), 28029 Madrid, Spain
7
Epithelial Biomedicine Division, CIEMAT, Avenida Complutense 40, 28040 Madrid, Spain
8
Department of Bioengineering, Universidad Carlos III de Madrid, Leganes, 28911 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(15), 3347; https://doi.org/10.3390/s19153347
Received: 28 May 2019 / Revised: 12 July 2019 / Accepted: 27 July 2019 / Published: 30 July 2019
(This article belongs to the Special Issue Microwave Sensors for Biomedical Applications)
Diabetes is a very complex condition affecting millions of people around the world. Its occurrence, always accompanied by sustained hyperglycemia, leads to many medical complications that can be greatly mitigated when the disease is treated in its earliest stage. In this paper, a novel sensing approach for the early non-invasive detection and monitoring of sustained hyperglycemia is presented. The sensing principle is based on millimeter-wave transmission spectroscopy through the skin and subsequent statistical analysis of the amplitude data. A classifier based on functional principal components for sustained hyperglycemia prediction was validated on a sample of twelve mice, correctly classifying the condition in diabetic mice. Using the same classifier, sixteen mice with drug-induced diabetes were studied for two weeks. The proposed sensing approach was capable of assessing the glycemic states at different stages of induced diabetes, providing a clear transition from normoglycemia to hyperglycemia typically associated with diabetes. This is believed to be the first presentation of such evolution studies using non-invasive sensing. The results obtained indicate that gradual glycemic changes associated with diabetes can be accurately detected by non-invasively sensing the metabolism using a millimeter-wave spectral sensor, with an observed temporal resolution of around four days. This unprecedented detection speed and its non-invasive character could open new opportunities for the continuous control and monitoring of diabetics and the evaluation of response to treatments (including new therapies), enabling a much more appropriate control of the condition. View Full-Text
Keywords: millimeter-wave spectroscopy; sustained hyperglycemia; non-invasive diagnosis techniques; early diabetes detection; functional principal component analysis millimeter-wave spectroscopy; sustained hyperglycemia; non-invasive diagnosis techniques; early diabetes detection; functional principal component analysis
Show Figures

Figure 1

MDPI and ACS Style

Moreno-Oyervides, A.; Martín-Mateos, P.; Aguilera-Morillo, M.C.; Ulisse, G.; Arriba, M.C.; Durban, M.; Del Rio, M.; Larcher, F.; Krozer, V.; Acedo, P. Early, Non-Invasive Sensing of Sustained Hyperglycemia in Mice Using Millimeter-Wave Spectroscopy. Sensors 2019, 19, 3347.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop