{"title":"简单脑电图对学习者活动识别的探讨","authors":"H. Abe, K. Baba, S. Takano, K. Murakami","doi":"10.1145/2618168.2618194","DOIUrl":null,"url":null,"abstract":"Understanding the states of learners at a lecture is expected to be useful for improving the quality of the lecture. This paper investigates the possibility of use of a simple electroencephalograph MindTune for activity recognition of a learner. The authors considered three kinds of activities for detecting states of a learner, and collected electroencephalography data with the activities by MindTune. Then, they applied K-nearest neighbor algorithm to the collected data, and the accuracy of the activity recognition was 58.2%. The result indicates a possibility of using MindTune for the activity recognition of learners.","PeriodicalId":192346,"journal":{"name":"International Conference on Information Systems and Design of Communication","volume":"298 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Towards activity recognition of learners by simple electroencephalographs\",\"authors\":\"H. Abe, K. Baba, S. Takano, K. Murakami\",\"doi\":\"10.1145/2618168.2618194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Understanding the states of learners at a lecture is expected to be useful for improving the quality of the lecture. This paper investigates the possibility of use of a simple electroencephalograph MindTune for activity recognition of a learner. The authors considered three kinds of activities for detecting states of a learner, and collected electroencephalography data with the activities by MindTune. Then, they applied K-nearest neighbor algorithm to the collected data, and the accuracy of the activity recognition was 58.2%. The result indicates a possibility of using MindTune for the activity recognition of learners.\",\"PeriodicalId\":192346,\"journal\":{\"name\":\"International Conference on Information Systems and Design of Communication\",\"volume\":\"298 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Information Systems and Design of Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2618168.2618194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Information Systems and Design of Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2618168.2618194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards activity recognition of learners by simple electroencephalographs
Understanding the states of learners at a lecture is expected to be useful for improving the quality of the lecture. This paper investigates the possibility of use of a simple electroencephalograph MindTune for activity recognition of a learner. The authors considered three kinds of activities for detecting states of a learner, and collected electroencephalography data with the activities by MindTune. Then, they applied K-nearest neighbor algorithm to the collected data, and the accuracy of the activity recognition was 58.2%. The result indicates a possibility of using MindTune for the activity recognition of learners.
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