Name
Abstract | ||
|---|---|---|
Emotion plays an important role in the interaction between humans as emotion is fundamental to human experience, influencing cognition, perception, learning communication, and even rational decision-making. Therefore, studying emotion is indispensable. This paper aims at finding the relationships between EEG signals and human emotions based on emotion recognition experiments that are conducted using the commercial Emotiv EPOC headset to record EEG signals while participants are watching emotional movies. Alpha, beta, delta and theta bands filtered from the recorded EEG signals are used to train and evaluate classifiers with different learning techniques including Support Vector Machine, k-Nearest Neighbour, Naïve Bayes and AdaBoost.M1. Our experimental results show that we can use the Emotiv headset for emotion recognition and that the AdaBoost.M1 technique and the theta band provide the highest recognition rates. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-34500-5_47 | ICONIP (5) |
Keywords | Field | DocType |
m1 technique,recorded eeg signal,emotiv headset,emotion recognition,emotiv epoc device,human emotion,highest recognition rate,eeg signal,commercial emotiv epoc headset,theta band,emotion recognition experiment,eeg | Headset,Naive Bayes classifier,Computer science,Emotion recognition,Support vector machine,Speech recognition,Cognition,Perception,Electroencephalography | Conference |
Volume | ISSN | Citations |
7667 | 0302-9743 | 12 |
PageRank | References | Authors |
1.02 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Trung Duy Pham | 1 | 16 | 2.09 |
| Dat Tran | 2 | 454 | 78.64 |