A precise non-invasive blood glucose measurement system using NIR spectroscopy and Huber’s regression model

  • Prateek JainEmail author
  • Ravi Maddila
  • Amit M. Joshi


Diabetes is one of the prominent diseases around the world. Presently, invasive techniques need a finger prick blood sample . A repetitively painful procedure that produces the chance of infection. To resolve this issue, non-invasive measurement approach is proposed. In this paper, an efficient NIR wave based optical detection system is proposed with optimized post-processing regression model. After real-time data analysis, it has been found that the coefficient of determination (\(R^{2}\)) is improved with the value of 0.9084 using proposed regression model. Mean absolute derivative is also increased with 3.87 mg/dl corresponding to predicted blood glucose concentration. Mean absolute relative difference has exceeded to 3.25%, and average error is improved with 3.77% using proposed regression model. Average accuaracy has been analyzed 94–95% for predicted blood glucose concentration.


NIR spectroscopy Non-invasive system Blood glucose measurement Regression model Statistical analysis 



The authors would like to thank Dispensary, Malaviya National of Technology and System Level Design and Calibration Testing Lab. The referenced blood glucose concentration values are taken from human blood. These values have been collected using one touch SD-check blood glucometer from laboratory, MNIT dispensary, MNIT Jaipur (Raj.). In this work, all financial and material support have been done by Malaviya National Institute of Technology, Jaipur (Raj.), India.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of ECEMNITJaipurIndia

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