TY  - JOUR
T1  - Feature Selection with Sequential Forward Selection Algorithm from Emotion Estimation based on EEG Signals
AU  - Alakuş, Talha Burak
AU  - Türkoğlu, İbrahim
PY  - 2019
DA  - December
Y2  - 2019
DO  - 10.16984/saufenbilder.501799
JF  - Sakarya University Journal of Science
JO  - SAUJS
PB  - Sakarya University
WT  - DergiPark
SN  - 2147-835X
SP  - 1096
EP  - 1105
VL  - 23
IS  - 6
LA  - en
AB  - In this study, we conducted EEG-based emotion recognition on arousal-valence emotion model. We collected our own EEG data with mobile EEG device Emotiv Epoc+ 14 channel by applying visual-aural stimulus. After collection we performed information measurement techniques, statistical methods and time-frequency attributes to obtain key features and created feature space. We wanted to observe the effect of features thus, we performed Sequential Forward Selection algorithm to reduce the feature space and compared the performance of accuracies for both all features and diminished features. In the last part, we applied QSVM (Quadratic Support Vector Machines) to classify the features and contrasted the accuracies. We observed that diminishing the feature space increased our average performance accuracy for arousal-valence dimension from 55% to 65%.
KW  - emotion estimation
KW  - feature selection
KW  - support vector machines
KW  - EEG
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UR  - https://doi.org/10.16984/saufenbilder.501799
L1  - https://dergipark.org.tr/en/download/article-file/793012
ER  -