2021年度 人工知能学会全国大会(第35回)

講演情報

国際セッション

国際セッション(Regular) » ER-5 Human interface, education aid

[1N2-IS-5a] Human interface, education aid (1/2)

2021年6月8日(火) 13:20 〜 15:00 N会場 (IS会場)

Chair: Toshihiro Hiraoka (The University of Tokyo)

14:00 〜 14:20

[1N2-IS-5a-03] Correlation analysis between the learning concentration estimated by EEG and the body motion measured by image sensors

〇Keita SHIMADA1, Shinji CHIBA2, Yusuke YOKOTA3, Yasushi NARUSE3, Ikuko Eguchi YAIRI1 (1. Sophia University, 2. Microsoft Japan Co., Ltd., 3. National Institute of Information and Communications Technology)

キーワード:Learning Concentration, Azure Kinect DK, EEG, ASSR

The purpose of this study is to develop a quantitative measurement method for humans' concentration on learning using an image sensor.This paper investigated the correlation between the concentration obtained by EEG measurement and the body motion obtained by the image sensor. The brain workload calculated from the EEG measurement results was used to measure the degree of learning concentration. The auditory steady-state response (ASSR) was used to estimate the workload. Two Kinects as the image sensor were used for the body motion measurement, and one was placed in front of the subject (Master) and the other was on the left hand side (Sub). Eleven healthy Japanese people participated in the experiment. The correlation between the calculated workload and the body motion information was investigated for two learning tasks. As a result, we succeeded in statistically showing the body parts that have a huge relation to the degree of learning concentration. In the future, we aim to develop algorithms and implement software application that can quantify the degree of learning concentration using only one Kinect.

講演PDFパスワード認証
論文PDFの閲覧にはログインが必要です。参加登録者の方は「参加者用ログイン」画面からログインしてください。あるいは論文PDF閲覧用のパスワードを以下にご入力ください。

パスワード