'工学部/工学系研究科 プレスリリース' blog (64135473799) of hub id 20511701

PRESS RELEASE

Breath odor-based individual authentication by an artificial olfactory sensor system and machine learning

 

Authors

Chaiyanut Jirayupat, Kazuki Nagashima, Takuro Hosomi, Tsunaki Takahashi, Benjarong Samransuksamer, Yosuke Hanai, Atsuo Nakao, Masaya Nakatani, Jiangyang Liu, Guozhu Zhang, Wataru Tanaka, Masaki Kanai, Takao Yasui, Yoshinobu Baba, and Takeshi Yanagida

 

Abstract

Breath odor sensing-based individual authentication was conducted for the first time using an artificial olfactory sensor system. Using a 16-channel chemiresistive sensor array and machine learning, a mean accuracy of >97% was successfully achieved. The impact of the number of sensors on the accuracy and reproducibility was also demonstrated.

 

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Chemical Communications: https://pubs.rsc.org/en/Content/ArticleLanding/2022/CC/D1CC06384G