Development of a non-invasive blood glucose monitor: application of artificial neural networks for signal processing

Author

Savage, Mark B. ; Kun, Stevan ; Harjunmaa, Hannu ; Peura, Robert A.

Author_Institution

Dept. of Biomed. Eng., Worcester Polytech. Inst., MA, USA

fYear

2000

fDate

2000

Firstpage

29

Lastpage

30

Abstract

We have developed a noninvasive blood glucose measuring instrument, based on application of the Optical Bridge^TM in the near-infrared region. This exploratory research is an endeavor to evaluate the possibility of increasing the performance of the noninvasive glucose monitor by employing Artificial Neural Networks (ANN). The objective of this research is to design an ANN to interpret the instrument´s outputs as well as the system parameters, and correlate them with blood glucose levels. The main hypothesis of this project is that such an ANN can be designed to improve the performance of this instrument

Keywords

backpropagation; bio-optics; biomedical measurement; biosensors; blood; feedforward neural nets; fuzzy neural nets; infrared spectroscopy; medical signal processing; optical sensors; patient monitoring; spectrochemical analysis; Optical Bridge; artificial neural networks; backpropagation; diabetes; differential absorbance; near-infrared region; noninvasive blood glucose monitor; signal processing; training; Artificial neural networks; Biomedical optical imaging; Blood; Diabetes; Instruments; Monitoring; Optical sensors; Optical signal processing; Sugar; Wavelength measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 2000. Proceedings of the IEEE 26th Annual Northeast

Conference_Location

Storrs, CT

Print_ISBN

0-7803-6341-8

Type

conf

DOI

10.1109/NEBC.2000.842363

Filename

842363