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An Artificial Intelligence Centred Multivariate Analysis for Blood Glucose Diagnosis

Author(s) : Senthil Kumar. A, Kavitha.S

Volume & Issue : VOLUME 2 / 2015 , ISSUE 1

Page(s) : 18-24
ISSN (Online): 2394-3858
ISSN (Print) : 2394-3866


Diabetes is a disease of disquiet evolving as one of the major health care epidemics of contemporary era. Hence Painless control of blood glucose levels would improve the quality of life, propounding better ruling of hyperglycaemia and hypoglycaemia thereby avoiding the complications of present day lancet methods. Although many efforts have been taken by researchers in order to successfully launch a device that measures blood glucose noninvasively, the results seems to be intruded due to mismatch in correlation with the present day devices. This is so because the Non-invasive device designers mostly concentrate on optical methods which suffer from greater interferences due to the less absorbing property of glucose. Aim of the paper is to draw together two different optical techniques namely Absorption photometry and photo acoustics using embedded technology, so that the results obtained produce better correlation after data handling with artificial neural network. Baseline pre-processing is used which will eliminate the errors due to instrument handling and temperature instability. Results obtained shows acceptable precision but in order to get satisfactory standards, Non-invasive glucose monitoring requires further efforts.


Diabetes, LASER light, Neural network, PhotoAcoustic, Photodiode, Transducers


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