{"title":"基于三次样条技术的脑事件相关电位特征提取","authors":"M. A. Raheem, E. A. Hussein","doi":"10.1109/AIC-MITCSA.2016.7759927","DOIUrl":null,"url":null,"abstract":"This paper illustrated the use of the Cubic spline Technique (CST) to analyze the EEG signals. It is provides full description of the extraction of the knots of EEG signals and then a discussion of how to select the optimum location of the knot and reducing the knots. Also the paper discussed that the feature extracted dependent on the optimal position of the knots. The initial results show the highest degree of accuracy to distinguish between five classes.","PeriodicalId":315179,"journal":{"name":"2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Feature extraction of brain event-related potentials using cubic spline technique\",\"authors\":\"M. A. Raheem, E. A. Hussein\",\"doi\":\"10.1109/AIC-MITCSA.2016.7759927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper illustrated the use of the Cubic spline Technique (CST) to analyze the EEG signals. It is provides full description of the extraction of the knots of EEG signals and then a discussion of how to select the optimum location of the knot and reducing the knots. Also the paper discussed that the feature extracted dependent on the optimal position of the knots. The initial results show the highest degree of accuracy to distinguish between five classes.\",\"PeriodicalId\":315179,\"journal\":{\"name\":\"2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIC-MITCSA.2016.7759927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIC-MITCSA.2016.7759927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature extraction of brain event-related potentials using cubic spline technique
This paper illustrated the use of the Cubic spline Technique (CST) to analyze the EEG signals. It is provides full description of the extraction of the knots of EEG signals and then a discussion of how to select the optimum location of the knot and reducing the knots. Also the paper discussed that the feature extracted dependent on the optimal position of the knots. The initial results show the highest degree of accuracy to distinguish between five classes.
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