TY - GEN
T1 - Men and Women Classification at Night through the Armpit Sweat Odor using Electronic Nose
AU - Sabilla, Irzal Ahmad
AU - Purbawa, Doni Putra
AU - Sarno, Riyanarto
AU - Fauzi, Asra Al
AU - Wijaya, Dedy Rahman
AU - Gunawan, Rudy
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/8
Y1 - 2021/4/8
N2 - Sweating at night can be an indication that there is a disturbance in the human metabolic system. Sweat itself is a substance that is unused in the body or the result of human excretion. The sweat glands are scattered in all parts of the body, but mostly in three locations: armpits, palms, and feet. Several kinds of research related to sweat and Electronic Nose (E-Nose) have also been studied. The study used a patch to absorb sweat and proved the presence of nicotine content from a smoker. However, the previous research has not focused on human sweat at night for potential disease. This paper aims to propose a system to distinguish men and women at night through the armpit sweat odor using Taguchi Gas Sensors (TGS) and SHT15. Researchers found four significant sensors for further investigation: TGS 822, TGS 826, TGS 833, and TGS 2620. This study obtained a total of 165 armpit sweat data, which have been processed and adjusted for this case into 25 data, 12 men (ME) and 13 women (WO). Several classification models are implemented, such as Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT) with accuracy 92.30%, 96.15%, and 84.62%, respectively. Based on the highest accuracy and the Volatile Organic Compounds (VOC) measurement, women are more likely to suffer from several diseases than men, such as leukemia.
AB - Sweating at night can be an indication that there is a disturbance in the human metabolic system. Sweat itself is a substance that is unused in the body or the result of human excretion. The sweat glands are scattered in all parts of the body, but mostly in three locations: armpits, palms, and feet. Several kinds of research related to sweat and Electronic Nose (E-Nose) have also been studied. The study used a patch to absorb sweat and proved the presence of nicotine content from a smoker. However, the previous research has not focused on human sweat at night for potential disease. This paper aims to propose a system to distinguish men and women at night through the armpit sweat odor using Taguchi Gas Sensors (TGS) and SHT15. Researchers found four significant sensors for further investigation: TGS 822, TGS 826, TGS 833, and TGS 2620. This study obtained a total of 165 armpit sweat data, which have been processed and adjusted for this case into 25 data, 12 men (ME) and 13 women (WO). Several classification models are implemented, such as Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT) with accuracy 92.30%, 96.15%, and 84.62%, respectively. Based on the highest accuracy and the Volatile Organic Compounds (VOC) measurement, women are more likely to suffer from several diseases than men, such as leukemia.
KW - ANNOVA
KW - Electronic Nose
KW - Gender
KW - Machine Learning
UR - http://www.scopus.com/inward/record.url?scp=85107972002&partnerID=8YFLogxK
U2 - 10.1109/APWiMob51111.2021.9435273
DO - 10.1109/APWiMob51111.2021.9435273
M3 - Conference contribution
AN - SCOPUS:85107972002
T3 - Proceedings - 2021 IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2021
SP - 121
EP - 127
BT - Proceedings - 2021 IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2021
Y2 - 8 April 2021 through 9 April 2021
ER -