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. 2009;9(9):7234-49.
doi: 10.3390/s90907234. Epub 2009 Sep 9.

Detection and classification of human body odor using an electronic nose

Chatchawal Wongchoosuk  1 , Mario Lutz, Teerakiat Kerdcharoen
Affiliations

Detection and classification of human body odor using an electronic nose

Chatchawal Wongchoosuk et al. Sensors (Basel). 2009.

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; PCA; biometrics; body odor; deodorant; humidity correction algorithm.

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Figures

Figure 1.
Figure 1.
Schematic diagram of the lab-made E-nose system.
Figure 2.
Figure 2.
(a) Typical raw data from a sensor and the max/min feature extraction on each curve. (b) Correction method of baseline shift as time proceeds.
Figure 3.
Figure 3.
Schematic diagram of humidity control using hardware-based method.
Figure 4.
Figure 4.
Resistance of sensors (a) TGS 813, (b) TGS 825 and (c) TGS 2602 versus relative humidity.
Figure 4.
Figure 4.
Resistance of sensors (a) TGS 813, (b) TGS 825 and (c) TGS 2602 versus relative humidity.
Figure 5.
Figure 5.
(a) Sensor response to isovaleric acid at different intensity level. (b) Logarithmic plot of the sensor response.
Figure 6.
Figure 6.
The sensor response with error bar of (a) person A and (b) person B in the morning and the afternoon. L and R denote the left and right armpits, respectively.
Figure 7.
Figure 7.
The 2D-PCA of armpit odors from two persons as measured in the afternoon during 5 days.
See this image and copyright information in PMC

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