Measuring academic affective states of students via brainwave signals
Added Title
International Conference on Knowledge and Systems Engineering (3rd : 2011)
KSE 2011
Department/Unit
Advance Research Institute for Informatics, Computing and Networking
Document Type
Conference Proceeding
Source Title
Proceedings - 2011 3rd International Conference on Knowledge and Systems Engineering, KSE 2011
First Page
226
Last Page
231
Publication Date
11-21-2011
Abstract
Multiple studies show that electroencephalogram (EEG) signals behave differently when humans experience various emotions. The objective of this project is to create a model of human academic emotions (namely: boredom, confusion, engagement and frustration) using EEG signals. Raw EEG signals were collected from nineteen (19) students while solving Berg's Card Sorting Task. Noise reduction was performed using 8Hz-30Hz 10th-Order Butter worth Band pass Filter. The following statistical features of raw EEG signals were computed: mean, standard deviation, mean of absolute first and second differences and standardized mean of absolute first and second differences. The k-Nearest Neighbor, Support Vector Machines, and Multilayer Perceptron were used as classifiers. Accuracy scores (at their highest) were 54.09%, 46.86% and 40.72% respectively, using batch cross-validation. © 2011 IEEE.
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Digitial Object Identifier (DOI)
10.1109/KSE.2011.43
Recommended Citation
Mampusti, E. T., Ng, J. S., Quinto, J. I., Teng, G. L., Suarez, M. C., & Trogo-Oblena, R. S. (2011). Measuring academic affective states of students via brainwave signals. Proceedings - 2011 3rd International Conference on Knowledge and Systems Engineering, KSE 2011, 226-231. https://doi.org/10.1109/KSE.2011.43
Disciplines
Computer Sciences
Keywords
Electroencephalography; Emotions and cognition
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