In the last decade, the use of electronic olfaction systems for the early diagnosis of several pathologies by breath analysis has been investigated. In this study, an electronic nose including seven polyaniline sensors has been developed. An impedance measurement circuit and a microcomputer to process the sensor responses were studied to give a prediagnosis conclusion. The measurement accuracy is 97% when it is exposed to a simulated human breath and different concentration of ammonia, from 500 ppb to 2.8 ppm. The described prototype weights about 300 g and can be used for 14 hours with a smartphone battery.
This paper presents a cost effective electronic nose prototype for the detection of 1.6 ppm of dimethyl methylphosphonate (DMMP) in a complex background. The device comprises of seven cross-sensitive carbon nanotube mat (CNT-mat) type sensors, an impedance measurement circuit and a microcomputer for data pre-treatment and classification stages. This study focused on the detection of DMMP in a gas mixture, using the responses of the sensors before they reach a stable and repeatable behavior. Even with this major constraint, the support vector machine used for classification reached 98% precision for the recognition of the samples.
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