BREATH ACETONE-BASED NON-INVASIVE DETECTION OF BLOOD GLUCOSE LEVELS

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

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Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 8 , ISSUE 2 (June 2015) > List of articles

BREATH ACETONE-BASED NON-INVASIVE DETECTION OF BLOOD GLUCOSE LEVELS

Anand Thati * / Arunangshu Biswas / Shubhajit Roy Chowdhury / Tapan Kumar Sau

Keywords : acetone sensor, exhaled breath, glucose, artificial neural network

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 2, Pages 1,244-1,260, DOI: https://doi.org/10.21307/ijssis-2017-805

License : (CC BY-NC-ND 4.0)

Received Date : 01-April-2015 / Accepted: 25-April-2015 / Published Online: 01-June-2015

ARTICLE

ABSTRACT

There has been a constant demand for the development of non-invasive, sensitive glucose sensor system that offers fast and real-time electronic readout of blood glucose levels. In this article, we propose a new system for detecting blood glucose levels by estimating the concentration of acetone in the exhaled breath. A TGS822 tin oxide (SnO2) sensor has been used to detect the concentration of acetone in the exhaled air. Acetone in exhaled breath showed a correlation with the blood glucose levels. Effects of pressure, temperature and humidity have been considered. Artificial Neural Network (ANN) has been used to extract features from the output waveform of the sensors. The system has been trained and tested with patient data in the blood glucose ranges from 80 mg/dl to 180 mg/dl. Using the proposed system, the blood glucose concentration has been estimated within an error limit of ±7.5 mg/dl.

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