{"title":"哮喘患者脑电图特征提取","authors":"Tan Teik Kean, A. Teo, M. Malarvili","doi":"10.1109/ICCEA.2010.286","DOIUrl":null,"url":null,"abstract":"In this paper, a total of 13 features were studied and automatically extracted to differentiate the asthmatic and nonasthmatic capnogram. From the results, slope ratio (SR) and the newly introduced Hjorth Parameters (HP2 - Mobility) are found to be the best among the investigated parameters in differentiating the two groups. Ongoing results show that parameters that associate with the slope of the capnogram are good index in differentiating the asthmatic and non-asthmatic capnogram.","PeriodicalId":207234,"journal":{"name":"2010 Second International Conference on Computer Engineering and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Feature Extraction of Capnogram for Asthmatic Patient\",\"authors\":\"Tan Teik Kean, A. Teo, M. Malarvili\",\"doi\":\"10.1109/ICCEA.2010.286\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a total of 13 features were studied and automatically extracted to differentiate the asthmatic and nonasthmatic capnogram. From the results, slope ratio (SR) and the newly introduced Hjorth Parameters (HP2 - Mobility) are found to be the best among the investigated parameters in differentiating the two groups. Ongoing results show that parameters that associate with the slope of the capnogram are good index in differentiating the asthmatic and non-asthmatic capnogram.\",\"PeriodicalId\":207234,\"journal\":{\"name\":\"2010 Second International Conference on Computer Engineering and Applications\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computer Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEA.2010.286\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computer Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEA.2010.286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature Extraction of Capnogram for Asthmatic Patient
In this paper, a total of 13 features were studied and automatically extracted to differentiate the asthmatic and nonasthmatic capnogram. From the results, slope ratio (SR) and the newly introduced Hjorth Parameters (HP2 - Mobility) are found to be the best among the investigated parameters in differentiating the two groups. Ongoing results show that parameters that associate with the slope of the capnogram are good index in differentiating the asthmatic and non-asthmatic capnogram.
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