By Topic

A Multi-Modal Emotion-Diagnosis System to Support e-Learning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
K. Nosu ; Tokai University, Japan ; T. Kurokawa

There has been a considerable amount of research done into the detection and evaluation of human emotions from implicit communication channels, including facial expressions. However, most studies have extracted facial features for some specific emotions in specific situations. This paper describes a system which can judge the emotions of an e-Learning user from his/her facial expression and biometrical signals. Criteria for classifying eight emotions were established using a time sequential subjective evaluation of the subject's emotions as well as the time sequential analysis of the subject's facial expressions and biometrical signals. The coincidence ratio between the discriminated emotions based upon the criteria of emotion diagnosis and the time sequential subjective evaluation of emotions for 10 e-Learning subjects was 74%. When only the facial expressions were taken into account, the coincidence ratio was 68%. These results confirm the effectiveness of the multi-modal emotion diagnosis

Published in:

First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06)  (Volume:2 )

Date of Conference:

Aug. 30 2006-Sept. 1 2006