Open Access Open Access  Restricted Access Subscription Access

Food Monitoring System to Analyze and Determine Glucose Level Using IR Sensor Based Model

Sarita B. Dhoble

Abstract


The prime intention of this research work has been to study and develop glucose monitoring system using IR sensor to determine the glucose level in food material. Glucose is one of main and essential source of energy for the human body. At the same time excess added sugar consumption is tied to poor health outcomes in children and old age person.  In this research work, IR sensor model is designed and develop which directly predicted the glucose concentration in food material. For further processing, these data base will be compare with predicted glucose values using various glucose monitoring techniques. The strength of the output signal increases or decreases due to motivational actions of ions and species in its viewing range and this analysis is made by using changes occurs in performance parameters of testing sample. As temperature changes cause a bias in the output of the sensor, therefore, any changes in the temperature of the sample, directly affect the analysis. This experimentation is used to conclude that the measured output current of the IR sensor decreased as glucose concentration in the sample material increased. The predicted result is used in food industry to check glucose level concentration.

 

Keyword: Glucose, sensor, IR, food


Full Text:

PDF

References


Wang J. Electrochemical glucose biosensors. Chem. Rev. 2008, 108, 814–825p.

Lee E.H. Glucose biosensors: An overview of use in clinical practice. Sensors, 2010, 10, 4558–4576p.

Klonoff D.C. Continuous glucose monitoring. Diabetes Care, 2005, 28, 1231–1239p.

DeSalvo, D. Buckingham B. Continuous glucose monitoring: Current use and future directions. Curr. Diabetes Rep. 2013, 13, 657–662p.

Ricci F., Moscone D., Palleschi G. Ex vivo continuous glucose monitoring with microdialysis technique: The example of glucoday. IEEE Sens. J., vol. 8, no. 1, 63–70p, Jan. 2008.

VazA., Ubarretxena A., Zalbide I., et al. Full passive UHF tag with a temperature sensor suit-able for human body temperature monitoring. IEEE Trans. Circuits Syst.II, Exp. Briefs, vol. 57, no. 2, 95–99p, Feb. 2010.

Akin T., Najafi K., Bradley R.M. A wireless implantable multi-channel digital neural recording system for a micro machined sieve electrode. IEEE J. Solid-State Circuits, vol. 33, no. 1, 109–118p, Jan. 1998.

Kon Ha, In-Je Yi, Grace Nisola, et al. A capillary electrophoresis (CE) microchip with an amperometric, electrochemical detector (ECD). Sensors 2009,Vol. 9, 4483-4502p.

Kon Ha, In-Je Yi, Grace Nisola, et al. Microchip Format Electrochemical Detector for the Sensing of Endocrine Disruptors. Proceedings of the 2nd IEEE International Conference on Nano/Micro Engineered and Molecular Systems, Bangkok, January 16 - 19, 2007.

Olszanowski A., Piechowiak K. The Use of an Electric field to Enhance bacterial movement and Hydrocarbon Biodegradation in Soils. Polish J. Environ. Stud., Vol. 15, No.2, (2006), 303-309p.

Margolin Y., Eisenbach M. Voltage Clamp Effects on Bacterial Chemotaxis. Journal of Bacteriology, August 1984, 605-610p0o.

Nacle H.T., Osuna R.G., Schiffman S.S. The how and why of electronics noses. IEEE Spectrum, September 1996, 22-31p.

Alocilja E.C., Ritchie N.L., Grooms D.L. Protocol development Using an Electronic Nose for Differentiating E. coli Strains. IEEE Sensors Journal, Vol. 3, NO. 6, December 2003, 801-806p.

Doraiswami R., Manoharan M., Woodruuf G.W. Nano Bio Embedded Fludic Substrates: System Level Integration for Food Safety. IEEE Electronic Components and Technology Conference, 2006, 158-160p.

Kea-Tiong Tang, Shih-Wen Chiu, Meng-Fan Chang, et al. A Low-Power Electronic Nose Signal-Processing Chip for a Portable Artificial Olfaction System. IEEE Transactions on Biomedical Circuits and Systems, Vol. 5, No. 4, August 2011, 380-391p.


Refbacks

  • There are currently no refbacks.