| Title: | Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds |
| Address: | "Intelligent Systems Laboratory, Department of Engineering Science, Sonoma State University, Rohnert Park, CA 94928, USA. boubinmj@miamioh.edu. Department of Electrical and Computer Engineering, Miami University, Oxford, OH 45056, USA. boubinmj@miamioh.edu. Intelligent Systems Laboratory, Department of Engineering Science, Sonoma State University, Rohnert Park, CA 94928, USA. sudhir.shrestha@sonoma.edu" |
| ISSN/ISBN: | 1424-8220 (Electronic) 1424-8220 (Linking) |
| Abstract: | "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" |
| Keywords: | *Biosensing Techniques Blood Glucose/*isolation & purification Breath Tests Diabetes Mellitus/*blood/pathology Gas Chromatography-Mass Spectrometry Humans Hypoglycemia/blood/pathology Support Vector Machine Volatile Organic Compounds/chemistry/*isolation; |
| Notes: | "MedlineBoubin, Matthew Shrestha, Sudhir eng 1502310/National Science Foundation/ Switzerland 2019/05/22 Sensors (Basel). 2019 May 17; 19(10):2283. doi: 10.3390/s19102283" |
