Reading activity recognition using an off-the-shelf eeg - Detecting reading activities and distinguishing genres of documents

Kai Kunze, Yuki Shiga, Shoya Ishimaru, Koichi Kise

研究成果: Conference article査読

16 被引用数 (Scopus)

抄録

The document analysis community spends substantial resources towards computer recognition of any type of text (e.g. characters, handwriting, document structure etc.). In this paper, we introduce a new paradigm focusing on recognizing the activities and habits of users while they are reading. We describe the differences to the traditional approaches of document analysis. We present initial work towards recognizing reading activities. We report our initial findings using a commercial, dry electrode Electroencephalography (EEG) system. We show the feasibility to distinguish reading tasks for 3 different document genres with one user and near perfect accuracy. Distinguishing reading tasks for 3 different document types we achieve 97 % with user specific training. We present evidence that reading and non-reading related activities can be separated over 3 users using 6 classes, perfectly separating reading from non-reading. A simple EEG system seems promising for distinguishing the reading of different document genres.

本文言語English
論文番号6628592
ページ(範囲)96-100
ページ数5
ジャーナルProceedings of the International Conference on Document Analysis and Recognition, ICDAR
DOI
出版ステータスPublished - 2013 12 11
外部発表はい
イベント12th International Conference on Document Analysis and Recognition, ICDAR 2013 - Washington, DC, United States
継続期間: 2013 8 252013 8 28

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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