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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


  1. Carlos F Amaral, et al (2009) ‘Multiparameter Technique for Non-Invasive Measurement of Blood Glucose’, Sensors and Actuators B Vol. 140, pp. 12-16.

  2. Carlos Eduardo Ferrnate Do Amaral and Benhard Wolf (2008) ‘Current Development in Non-Invasive Glucose Monitoring’, Medical Engineering and Physics, Vol.30, pp.541-549.

  3. Andrea Tura, et al (2006) ‘Non Invasive Glucose Monitoring: Assessment of Technologies and devices according to quantitative criteria’- Diabetes Research and clinical practice, Vol.77, pp.16-40.

  4. Bachem A and Reed C.I (1931) ‘The Penetration of light through human skin’, Amer.J.Physiol, vol.97, pp.86-91.

  5. Cote, et al (1992) ‘Non- Invasive Optical Polarimetric glucose sensing using a true phase measurement technique’, IEEE Transactions on Biomedical Engineering, vol.39, No.7, pp. 752-756.

  6. Crothall Y. Yu. K. D, et al. (2003) ‘LASER diode applications in a continuous blood glucose sensor’, proc. SPIE, vol.4996, pp. 268-274.

  7. David C. Klonoff (1997) ‘Non Invasive Blood Glucose Monitoring’- Journal of Diabetes Care, Vol.20, No.3, pp. 433-437.

  8. Lili Zhu, et al (2013), ‘

  9. Sargent M. and M.O.Scully (1972) ‘Theory of LASER operation- An outline’, LASER handbook, vol. I, pp. 45-114

  10. Zhao. Z and Myllyl. R (2001), ‘Photoacoustic blood glucose and tissue measurements based on optical scattering effect’, Proceedings of the SPIE, Vol. 4707, pp. 153-157.

  11. Bashkatov A. N (2005), ‘Optical Properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm’, Journal of Physics D:Applied Physics, Vol. 38, pp. 2543-2555.

  12. Zhao. Z and R. Myllyl, (2002), ’Pulsed Photoacoustic investigations in liquid and Tissue’, Molecular and Quantum Acoustics, Vol. 23, pp. 451-462.

  13. McNichols J.R. and Cote L.G (2000) ‘Optical glucose sensing in biological fluids: An overview’ - Journal of biomedical Optics, vol.5, No.1, pp. 8-16.

  14. Khalil O.S. (1999), ‘Spectroscopic and clinical aspects of Non-Invasive glucose measurements’, clinical chemistry, vol.45, No. 2, pp.165-177.

  15. Amerov A.K, et al (2005) ‘Scattering and Absorption effects in the determination of glucose in whole body by near infrared spectroscopy’ Anal. Chem, No.77, pp. 4587-4594.