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A Low-Power Wearable E-Nose System Based on a Capacitive Micromachined Ultrasonic Transducer (CMUT) Array for Indoor VOC Monitoring
Volatile organic compounds (VOCs) are pervasive in the environment and their real-time continuous monitoring can facilitate better understanding of their effects on human health by combining environmental factors with physiological conditions. The scope of wearable sensors for detection of VOCs is e...
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Published in: | IEEE sensors journal 2021-09, Vol.21 (18), p.19684-19696 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Volatile organic compounds (VOCs) are pervasive in the environment and their real-time continuous monitoring can facilitate better understanding of their effects on human health by combining environmental factors with physiological conditions. The scope of wearable sensors for detection of VOCs is evident as the accuracy of the sensor prediction depends on its proximity to the VOC source along with the sensitivity and selectivity of the sensor itself. In this paper, we present a low-power wearable e-nose system based on a capacitive micromachined ultrasonic transducer (CMUT) array. CMUTs offer inherent benefits of excellent mass resolution, easy array fabrication, and integration with electronics, which make them an appropriate choice as a transducer element for gravimetric e-nose systems. A 5-channel CMUT sensor array was chemically functionalized and used for the detection of four volatiles, ethanol, toluene, p-xylene, and styrene. All the channels of the sensor array achieved a resolution below 10 ppm within 0.2-3% of OSHA-PEL time-weighted average (TWA) for each volatile. For each test cycle, the maximum frequency shift, the rate of adsorption, and the rate of desorption were extracted as features. Linear discriminant analysis (LDA) was applied to visualize the discrimination performance of the sensor array. The system performance was characterized using an automated testing system. The presented sensor system can be used for identification of volatiles with suitable pattern-recognition techniques. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2021.3094125 |