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Authors: Alicia Heraz and Claude Frasson

Affiliation: HERON Lab, University of Montréal, Canada

ISBN: 978-989-8111-66-1

Keyword(s): Electrical Brain Activity, Machine Learning Techniques, Learner Brainwaves Model.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Intelligent User Interfaces ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Multi-Agent Systems ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Software Engineering ; Symbolic Systems

Abstract: In this paper we discuss how learner’s electrical brain activity can be influenced by emotional stimuli. We conducted an experimentation in which we exposed a group of 17 learners to a series of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded. We got 33.106 recordings. In an exploratory study we examined the influence of 24 picture categories from the IAPS on the amplitude variations of the 4 brainwaves frequency bands: δ, φ, α and β. We used machine learning techniques to track the amplitudes in order to predict the dominant frequency band which inform about the learner mental and emotional states. Correlation and regression analyses show a significant impact of the emotional stimuli on the amplitudes of the brainwave frequency bands. Standard classification techniques were used to assess the reliability of the automatic prediction of the dominant frequency band. The reached accuracy was 90%. We discuss the prospects of extending our actual Brainwave-Sensing Multi Agent System to be integrated to an intelligent tutoring system (ITS) in the future. (More)

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Paper citation in several formats:
Heraz A.; Frasson C. and (2009). HOW DO EMOTIONAL STIMULI INFLUENCE THE LEARNER’S BRAIN ACTIVITY? - Tracking the Brainwave Frequency Bands Amplitudes .In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 14-20. DOI: 10.5220/0001558100140020

@conference{icaart09,
author={Alicia Heraz and Claude Frasson},
title={HOW DO EMOTIONAL STIMULI INFLUENCE THE LEARNER’S BRAIN ACTIVITY? - Tracking the Brainwave Frequency Bands Amplitudes },
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={14-20},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001558100140020},
isbn={978-989-8111-66-1},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - HOW DO EMOTIONAL STIMULI INFLUENCE THE LEARNER’S BRAIN ACTIVITY? - Tracking the Brainwave Frequency Bands Amplitudes
SN - 978-989-8111-66-1
AU - Heraz, A.
AU - Frasson, C.
PY - 2009
SP - 14
EP - 20
DO - 10.5220/0001558100140020

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