Table 1.
Other studies about classification of emotion using physiological signals.
| No. | Emotions | Signals | Classifiers | Accuracy [%] |
|---|---|---|---|---|
| 1 [8] | Arousal, Valence | EEG | SVM | 82.0 |
| 2 [9] | Amusement, Fear, Sadness, Joy, Anger, Disgust | EEG, ECG | Bayesian Network | 98.1 |
| 3 [10] | Amusement, Grief, Anger, Fear, Baseline | OXY, GSR, ECG | RF | 74.0 |
| 4 [11] | Arousal, Valence | EMG, RSP | SVM | 74.0 |
| 5 [12] | Arousal, Valence | EEG | LSTM | 72.1 for valance 74.1 for arousal |
| 6 [13] | Arousal, Valence | EEG | KNN, RF | 69.9 for valance 71.2 for arousal |
| 7 [14] | Arousal, Valence | EEG, EMG, EOG, GSR, RSP, T, BVP | SVM | 88.3 for valence 90.6 for arousal |
| 8 [15] | Positive, Negative | ECG | SVM | 73.1 |
| 9 [16] | Arousal, Valence | EEG | G extreme Learning Machine | 91.1 |
| 10 [17] | Happy, Curious, Angry, Sad, Quiet | EEG | QDA | 47.5 |