Sensors 2009, 9(9), 7234-7249; doi:10.3390/s90907234
Article

Detection and Classification of Human Body Odor Using an Electronic Nose

1 Department of Physics and Center of Nanoscience and Nanotechnology, Faculty of Science, Mahidol University, Ratchathewee, Bangkok 10400, Thailand 2 Materials Science and Engineering Programme, Faculty of Science, Mahidol University, Ratchathewee, Bangkok 10400, Thailand 3 NANOTEC Center of Excellence at Mahidol University, National Nanotechnology Center, Bangkok 10400, Thailand
* Author to whom correspondence should be addressed.
Received: 24 June 2009; in revised form: 19 August 2009 / Accepted: 3 September 2009 / Published: 9 September 2009
(This article belongs to the Special Issue Sensor Algorithms)
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Abstract: An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.
Keywords: E-nose; body odor; biometrics; PCA; deodorant; humidity correction algorithm

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MDPI and ACS Style

Wongchoosuk, C.; Lutz, M.; Kerdcharoen, T. Detection and Classification of Human Body Odor Using an Electronic Nose. Sensors 2009, 9, 7234-7249.

AMA Style

Wongchoosuk C, Lutz M, Kerdcharoen T. Detection and Classification of Human Body Odor Using an Electronic Nose. Sensors. 2009; 9(9):7234-7249.

Chicago/Turabian Style

Wongchoosuk, Chatchawal; Lutz, Mario; Kerdcharoen, Teerakiat. 2009. "Detection and Classification of Human Body Odor Using an Electronic Nose." Sensors 9, no. 9: 7234-7249.

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