Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds
This paper presents an embedded system-based solution for sensor arrays to estimate blood glucose levels from volatile organic compounds (VOCs) in a patient’s breath. Support vector machine (SVM) was trained on a general-purpose computer using an existing SVM library. A training model, opt...
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Format: | Article |
Language: | English |
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MDPI AG
2019-05-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/19/10/2283 |
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author | Matthew Boubin Sudhir Shrestha |
author_facet | Matthew Boubin Sudhir Shrestha |
author_sort | Matthew Boubin |
collection | DOAJ |
description | This paper presents an embedded system-based solution for sensor arrays to estimate blood glucose levels from volatile organic compounds (VOCs) in a patient’s breath. Support vector machine (SVM) was trained on a general-purpose computer using an existing SVM library. A training model, optimized to achieve the most accurate results, was implemented in a microcontroller with an ATMega microprocessor. Training and testing was conducted using artificial breath that mimics known VOC footprints of high and low blood glucose levels. The embedded solution was able to correctly categorize the corresponding glucose levels of the artificial breath samples with 97.1% accuracy. The presented results make a significant contribution toward the development of a portable device for detecting blood glucose levels from a patient’s breath. |
first_indexed | 2024-04-12T19:38:24Z |
format | Article |
id | doaj.art-3f81981bb9d0479d9c6eb2e94a86bdf0 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-04-12T19:38:24Z |
publishDate | 2019-05-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-3f81981bb9d0479d9c6eb2e94a86bdf02022-12-22T03:19:08ZengMDPI AGSensors1424-82202019-05-011910228310.3390/s19102283s19102283Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic CompoundsMatthew Boubin0Sudhir Shrestha1Intelligent Systems Laboratory, Department of Engineering Science, Sonoma State University, Rohnert Park, CA 94928, USAIntelligent Systems Laboratory, Department of Engineering Science, Sonoma State University, Rohnert Park, CA 94928, USAThis paper presents an embedded system-based solution for sensor arrays to estimate blood glucose levels from volatile organic compounds (VOCs) in a patient’s breath. Support vector machine (SVM) was trained on a general-purpose computer using an existing SVM library. A training model, optimized to achieve the most accurate results, was implemented in a microcontroller with an ATMega microprocessor. Training and testing was conducted using artificial breath that mimics known VOC footprints of high and low blood glucose levels. The embedded solution was able to correctly categorize the corresponding glucose levels of the artificial breath samples with 97.1% accuracy. The presented results make a significant contribution toward the development of a portable device for detecting blood glucose levels from a patient’s breath.https://www.mdpi.com/1424-8220/19/10/2283breath disease detectionbreath volatile organic compoundsdiabetessupport vector machinemicrocontroller implementation of SVM |
spellingShingle | Matthew Boubin Sudhir Shrestha Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds Sensors breath disease detection breath volatile organic compounds diabetes support vector machine microcontroller implementation of SVM |
title | Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds |
title_full | Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds |
title_fullStr | Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds |
title_full_unstemmed | Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds |
title_short | Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds |
title_sort | microcontroller implementation of support vector machine for detecting blood glucose levels using breath volatile organic compounds |
topic | breath disease detection breath volatile organic compounds diabetes support vector machine microcontroller implementation of SVM |
url | https://www.mdpi.com/1424-8220/19/10/2283 |
work_keys_str_mv | AT matthewboubin microcontrollerimplementationofsupportvectormachinefordetectingbloodglucoselevelsusingbreathvolatileorganiccompounds AT sudhirshrestha microcontrollerimplementationofsupportvectormachinefordetectingbloodglucoselevelsusingbreathvolatileorganiccompounds |