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

We have developed a noninvasive blood glucose measuring instrument, based on application of the Optical Bridge/sup 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 Artif...

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Bibliographic Details
Published inProceedings of the IEEE 26th Annual Northeast Bioengineering Conference (Cat. No.00CH37114) pp. 29 - 30
Main Authors Savage, M.B., Kun, S., Harjunmaa, H., Peura, R.A.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 2000
Subjects
Artificial neural networks
Biomedical optical imaging
Blood
Diabetes
Instruments
Monitoring
Optical sensors
Optical signal processing
Sugar
Wavelength measurement
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Summary:We have developed a noninvasive blood glucose measuring instrument, based on application of the Optical Bridge/sup 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.
ISBN:9780780363410
0780363418
DOI:10.1109/NEBC.2000.842363