{"title":"模拟室内空气中与疾病相关的挥发性有机化合物的监测","authors":"T. Itoh, T. Akamatsu, N. Izu, W. Shin, H. Byun","doi":"10.1109/ICSENS.2014.6985281","DOIUrl":null,"url":null,"abstract":"We have investigated the reduction in the influence of room air contamination on the monitoring of lung cancer-related volatile organic compounds (VOCs), namely, nonanal, n-decane, and acetoin, and sugar diabetes-related VOCs, namely, acetone and methyl i-butyl ketone. We have used a gas comprising a mixture of 300 μg/m3 of 31 kinds of VOCs as this has been proposed to resemble an indoor air-like gas. We have used six sensors comprising four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2) to monitor the gases for detecting lung cancer-related VOCs and sugar diabetes-related VOCs. We analyzed sensor signals using principal component analysis. When a total of six sensors (TGS and Pt, Pd, Au/SnO2 sensors) was used, we could successfully discriminate between lung cancer- and sugar diabetes-related VOCs. The sensor that has small value for the difference in sensor response, which is the difference in sensor response between 1 ppm of target gases in pure air and those in simulated room air, should be selected from the array of six sensors for a more improved discrimination accuracy under simulated room air conditions.","PeriodicalId":13244,"journal":{"name":"IEEE SENSORS 2014 Proceedings","volume":"13 1","pages":"1427-1430"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Monitoring of disease-related volatile organic compounds in simulated room air\",\"authors\":\"T. Itoh, T. Akamatsu, N. Izu, W. Shin, H. Byun\",\"doi\":\"10.1109/ICSENS.2014.6985281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have investigated the reduction in the influence of room air contamination on the monitoring of lung cancer-related volatile organic compounds (VOCs), namely, nonanal, n-decane, and acetoin, and sugar diabetes-related VOCs, namely, acetone and methyl i-butyl ketone. We have used a gas comprising a mixture of 300 μg/m3 of 31 kinds of VOCs as this has been proposed to resemble an indoor air-like gas. We have used six sensors comprising four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2) to monitor the gases for detecting lung cancer-related VOCs and sugar diabetes-related VOCs. We analyzed sensor signals using principal component analysis. When a total of six sensors (TGS and Pt, Pd, Au/SnO2 sensors) was used, we could successfully discriminate between lung cancer- and sugar diabetes-related VOCs. The sensor that has small value for the difference in sensor response, which is the difference in sensor response between 1 ppm of target gases in pure air and those in simulated room air, should be selected from the array of six sensors for a more improved discrimination accuracy under simulated room air conditions.\",\"PeriodicalId\":13244,\"journal\":{\"name\":\"IEEE SENSORS 2014 Proceedings\",\"volume\":\"13 1\",\"pages\":\"1427-1430\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE SENSORS 2014 Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSENS.2014.6985281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE SENSORS 2014 Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENS.2014.6985281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Monitoring of disease-related volatile organic compounds in simulated room air
We have investigated the reduction in the influence of room air contamination on the monitoring of lung cancer-related volatile organic compounds (VOCs), namely, nonanal, n-decane, and acetoin, and sugar diabetes-related VOCs, namely, acetone and methyl i-butyl ketone. We have used a gas comprising a mixture of 300 μg/m3 of 31 kinds of VOCs as this has been proposed to resemble an indoor air-like gas. We have used six sensors comprising four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2) to monitor the gases for detecting lung cancer-related VOCs and sugar diabetes-related VOCs. We analyzed sensor signals using principal component analysis. When a total of six sensors (TGS and Pt, Pd, Au/SnO2 sensors) was used, we could successfully discriminate between lung cancer- and sugar diabetes-related VOCs. The sensor that has small value for the difference in sensor response, which is the difference in sensor response between 1 ppm of target gases in pure air and those in simulated room air, should be selected from the array of six sensors for a more improved discrimination accuracy under simulated room air conditions.