Automatic quantitative evaluation of emotions in E-learning applications.
The long term goal of our research is to develop a tool for recognizing human emotions during e-learning processes. This could be accomplished by combining quantitative indexes extracted from non-invasive recordings of four physiological signals: namely skin conductance, blood volume pulse, electrocardiogram and electroencephalogram. Wearable, non-invasive sensors, communicating with a PC, were applied to 30 students and data were collected during exposure to three different computer-mediated content stimuli designed to evoke specific emotional states: stress, relaxation and engagement. In this paper we describe both the general emotion evaluation algorithm, and present a preliminary results suggesting that some of the quantitative indexes may be successful in characterizing and distinguishing between the three different emotional states.
Scotti
Stefano
S
Bioengineering Department, Polytechnic University, Milan, Italy. stefano.scotti@polimi.it
Mauri
Maurizio
M
Barbieri
Riccardo
R
Jawad
Bassam
B
Cerutti
Sergio
S
Mainardi
Luca
L
Brown
Emery N
EN
Villamira
Marco A
MA
D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D003194:Computer-Assisted Instruction / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004644:Emotions / Q000145:classification* / Q000502:physiology*; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D008991:Monitoring, Physiologic / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*