Abstract : Understanding the states of learners at a lecture is expected to be useful for improving the quality of the lecture. This paper is trying to recognize the activities of learners by their brain wave data for estimating the states. In analyses on brain wave data, generally, some particular bands such as α and β are considered as the features. The authors considered other bands of higher and lower frequencies to compensate for the coarseness of simple electroencephalographs. They conducted an experiment of recognizing two activities of five subjects with the brain wave data captured by a simple electroencephalograph. They applied support vector machine to 8-dimensional vectors which correspond to eight bands on the brain wave data. The results show that considering multiple bands yielded high accuracy compared with the usual features.
Type de document :
Communication dans un congrès
Ismail Khalil; Erich Neuhold; A Min Tjoa; Li Da Xu; Ilsun You. 3rd International Conference on Information and Communication Technology-EurAsia (ICT-EURASIA) and 9th International Conference on Research and Practical Issues of Enterprise Information Systems (CONFENIS), Oct 2015, Daejon, South Korea. Springer, Lecture Notes in Computer Science, LNCS-9357, pp.64-73, 2015, Information and Communication Technology. 〈10.1007/978-3-319-24315-3_7〉
https://hal.inria.fr/hal-01466252
Contributeur : Hal Ifip
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Soumis le : lundi 13 février 2017 - 14:37:12
Dernière modification le : lundi 13 février 2017 - 14:45:35
Document(s) archivé(s) le : dimanche 14 mai 2017 - 14:09:44
Hiromichi Abe, Kazuya Kinoshita, Kensuke Baba, Shigeru Takano, Kazuaki Murakami. Analyzing Brain Waves for Activity Recognition of Learners. Ismail Khalil; Erich Neuhold; A Min Tjoa; Li Da Xu; Ilsun You. 3rd International Conference on Information and Communication Technology-EurAsia (ICT-EURASIA) and 9th International Conference on Research and Practical Issues of Enterprise Information Systems (CONFENIS), Oct 2015, Daejon, South Korea. Springer, Lecture Notes in Computer Science, LNCS-9357, pp.64-73, 2015, Information and Communication Technology. 〈10.1007/978-3-319-24315-3_7〉. 〈hal-01466252〉
