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Conference Paper The Miniaturized IoT Electronic Nose Device and Sensor Data Collection System for Health Screening by Volatile Organic Compounds Detection from Exhaled Breath
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Authors
Jongwoo Choi, SungJune Chang, Joon-Hak Bang, Jun Seok Park, Hae Ryong Lee
Issue Date
2018-12
Citation
International Symposium on Information and Communication Technology (SoICT) 2018, pp.405-409
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1145/3287921.3287943
Abstract
The recent convergence of ICT technology and biotechnology has led to an increasing number of areas in which machines take over what people do. The small sized medical electronic devices easily check health condition by simple test and confirm whether the bio signals are abnormal to advise medical treatment in the hospital. The role of such health screening devices is not to diagnose the disease precisely but to check bio-signal roughly. The conventional health screening devices pick blood sample to detect amount of specific component in blood but invasive blood sampling is painful and burdensome to the patient. Breath analysis is a technique that provides comfortable and easy health screening method unlike conventional techniques because it is non-invasive. However, it is difficult for people to use it because of its complex breath sampling procedures, huge system volume, and sensitive characteristics of gas sensors. We designed a smartphone-sized miniaturized electronic nose system and constructed database system to derive novel rules from various multi-sensors data. The experiment was conducted by applying the electronic nose system to actual diabetic patients and we confirmed the possibility of distinguishing the diseases had. If big data is collected, various artificial intelligence algorithms will be applied to find more accurate health screening methods.
KSP Keywords
Artificial intelligence algorithms, Big Data, Blood sample, Blood sampling, Data collection system, Database systems, Electronic Nose(E-Nose), Electronic nose system, Health condition, Medical electronics, Multi-Sensors Data