Learner's Positive and Negative Emotion Prediction using i-Emotion
Bio Sensor in emotion includes the use of a sensor known as Brain Computer Interface (BCI) in recognizing the emotion signals that occur in the human brain (electroencephalograph signals). The researcher used a BCI tool to collect the required data of attention and meditation value scale through...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/17314/ http://umpir.ump.edu.my/id/eprint/17314/1/271_281.pdf |
| Summary: | Bio Sensor in emotion includes the use of a sensor known as Brain Computer Interface (BCI) in
recognizing the emotion signals that occur in the human
brain (electroencephalograph signals). The researcher
used a BCI tool to collect the required data of attention
and meditation value scale through a qualitative
sampling. The respondent for this research are school
kids’ age between 7 to 12 years old. In order to classify
their positive and negative emotions, these EEG signals
involves a lot of data and need to be mined in order to
make it valuable and meaningful. By using rule-based
(PART) classifier, the decision lists represent the
regularities of the attention and meditation levels
among kids. The data were generated and converted
into several rule sets named rule-based prediction set
and have been implemented in the i-Emotion using
MATLAB environment. A baseline set which is adapted
from an established eSense meter values was also
coded into the prototype. |
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