Selective prediction of student emotions based on unusually strong EEG signals
With an electroencephalogram (EEG) sensor mounted on their head while learning mathematics using two computer-based learning software, EEG signals were collected from fifty six (56) academically-gifted students of ages 11 to 14. The EEG signals are used to predict four academic emotions, namely frus...
Saved in:
Main Authors: | Azcarraga, Judith Jumig, Marcos, Nelson, Azcarraga, Arnulfo P., Hayashi, Yoichi |
---|---|
Format: | text |
Published: |
Animo Repository
2015
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1279 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Similar Items
-
Prospects in modeling reader's affect based on EEG signals
by: Kalaw, Kristine, et al.
Published: (2017) -
Recognizing student emotions using brainwaves and mouse behavior data
by: Azcarraga, Judith Jumig, et al.
Published: (2013) -
Gender-specific classifiers in phoneme recognition and academic emotion detection
by: Azcarraga, Arnulfo P., et al.
Published: (2016) -
Analyzing novice programmers' EEG signals using unsupervised algorithms
by: Swansi, Vanlalhruaii, et al.
Published: (2017) -
Predicting academic emotion based on brainwaves signals and mouse click behavior
by: Azcarraga, Judith, et al.
Published: (2011)