Prospects in modeling reader's affect based on EEG signals

Prospects in modeling reader's affect based on EEG signals

© 2017 Asia-Pacific Society for Computers in Education. All rights reserved. Readers experience various emotions while reading, which may affect their overall enjoyment and comprehension of the material. The current work presents a study on brainwaves or EEG signals and their association to emotions...

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Main Authors: Kalaw, Kristine, Ong, Ethel, Azcarraga, Judith Jumig
Format: text
Published: Animo Repository 2017
Subjects:
Electroencephalography
Machine learning
Emotion recognition
Computer Sciences
Software Engineering
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1453
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Institution: De La Salle University
id oai:animorepository.dlsu.edu.ph:faculty_research-2452
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:faculty_research-24522022-11-16T03:07:44Z Prospects in modeling reader's affect based on EEG signals Kalaw, Kristine Ong, Ethel Azcarraga, Judith Jumig © 2017 Asia-Pacific Society for Computers in Education. All rights reserved. Readers experience various emotions while reading, which may affect their overall enjoyment and comprehension of the material. The current work presents a study on brainwaves or EEG signals and their association to emotions while a person is reading literary fiction. EEG data from 32 participants, aged 18 years old and above, were collected with the use of an EEG headset. We describe our methodology for data acquisition and processing, feature extraction and dataset building, as well as the classification experiments done. 2017-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/1453 Faculty Research Work Animo Repository Electroencephalography Machine learning Emotion recognition Computer Sciences Software Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Electroencephalography
Machine learning
Emotion recognition
Computer Sciences
Software Engineering
spellingShingle Electroencephalography
Machine learning
Emotion recognition
Computer Sciences
Software Engineering
Kalaw, Kristine
Ong, Ethel
Azcarraga, Judith Jumig
Prospects in modeling reader's affect based on EEG signals
description © 2017 Asia-Pacific Society for Computers in Education. All rights reserved. Readers experience various emotions while reading, which may affect their overall enjoyment and comprehension of the material. The current work presents a study on brainwaves or EEG signals and their association to emotions while a person is reading literary fiction. EEG data from 32 participants, aged 18 years old and above, were collected with the use of an EEG headset. We describe our methodology for data acquisition and processing, feature extraction and dataset building, as well as the classification experiments done.
format text
author Kalaw, Kristine
Ong, Ethel
Azcarraga, Judith Jumig
author_facet Kalaw, Kristine
Ong, Ethel
Azcarraga, Judith Jumig
author_sort Kalaw, Kristine
title Prospects in modeling reader's affect based on EEG signals
title_short Prospects in modeling reader's affect based on EEG signals
title_full Prospects in modeling reader's affect based on EEG signals
title_fullStr Prospects in modeling reader's affect based on EEG signals
title_full_unstemmed Prospects in modeling reader's affect based on EEG signals
title_sort prospects in modeling reader's affect based on eeg signals
publisher Animo Repository
publishDate 2017
url https://animorepository.dlsu.edu.ph/faculty_research/1453
_version_ 1751550431663751168

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