Smart wristband with integrated chemical sensors for detecting glucose levels using breath volatile organic compounds

S. Shrestha; C. Harold; M. Boubin; L. Lawrence

doi:10.1117/12.2521365

2 May 2019 Smart wristband with integrated chemical sensors for detecting glucose levels using breath volatile organic compounds

S. Shrestha, C. Harold, M. Boubin, L. Lawrence

Author Affiliations +

Proceedings Volume 11020, Smart Biomedical and Physiological Sensor Technology XVI; 110200R (2019) https://doi.org/10.1117/12.2521365
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

This paper presents a microcontroller-based solution to classify blood glucose levels using acetone and ethanol breath volatile organic compounds. Two metal oxide semiconductor-based chemical sensors able to detect acetone and ethanol at parts per million concentrations were used. The sensors were tested in a controlled setup with humidified air spiked with acetone and ethanol, mimicking human breath corresponding to low and high blood glucose groups. A support vector machine algorithm was trained and implemented in a microcontroller. In a real time-time test, the trained algorithm classified low and high blood glucose groups with 97% accuracy. Subsequently, a smart wristband prototype that integrates the two sensors was developed. An Arduino-based wearable microcontroller platform was used for its small formfactor and a low-power operation. The wristband is enclosed in a 3D printed housing and powered by an onboard 3.7 V 500 mAh rechargeable Li-ion battery. A smartphone app communicates with the wristband through Bluetooth, allows data visualization, and saves data in the cloud. The presented work makes a significant contribution towards the development of a wearable device for detecting blood glucose levels from a patient’s breath.

Citation Download Citation

S. Shrestha, C. Harold, M. Boubin, and L. Lawrence "Smart wristband with integrated chemical sensors for detecting glucose levels using breath volatile organic compounds", Proc. SPIE 11020, Smart Biomedical and Physiological Sensor Technology XVI, 110200R (2 May 2019); https://doi.org/10.1117/12.2521365

ACCESS THE FULL ARTICLE