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Modelling of blood glucose profiles non-invasively using a neural network algorithm

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2 Author(s)
Ghevondian, N. ; Fac. of Eng., Univesity of Technol., Sydney, NSW, Australia ; Nguyen, H.

Monitoring blood glucose levels of Insulin-Dependent-Diabetes-Mellitus (IDDM) is essential for detecting onset of hypoglycaemia and hyperglycaemia. We have developed a method based on a neural network algorithm for estimating blood glucose levels non-invasively using only physiological parameters such as skin impedance and heart rate. Results have shown that an accuracy of 10% can be achieved

Published in:

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint  (Volume:2 )

Date of Conference:

Oct 1999