EEG-based valence level recognition for real-time applications
Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence leve...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
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2013
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| Online Access: | https://hdl.handle.net/10356/84767 http://hdl.handle.net/10220/12706 |
| _version_ | 1811690407328743424 |
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| author | Liu, Yisi. Sourina, Olga. |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Liu, Yisi. Sourina, Olga. |
| author_sort | Liu, Yisi. |
| collection | NTU |
| description | Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence level recognition algorithm, where the thresholds were used to identify different levels of the valence dimension of the human emotion. The algorithm was tested by using the EEG data labeled with valence levels. The algorithm could identify valence levels continuously. The algorithm was tested with the experiment data and with the benchmark affective EEG database DEAP where up to 9 levels of valence dimension with high/low dominance were recognized. Then, the algorithm was applied to recognize 16 emotions defined by high/low arousal, high/low dominance and 4 levels of valence. At least 14 electrodes should be used to get the better accuracy. The proposed algorithm could be implemented in different real-time applications such as emotional avatar and E-learning systems. |
| first_indexed | 2024-10-01T06:03:30Z |
| format | Conference Paper |
| id | ntu-10356/84767 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:03:30Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/847672020-03-07T13:24:45Z EEG-based valence level recognition for real-time applications Liu, Yisi. Sourina, Olga. School of Electrical and Electronic Engineering International Conference on Cyberworlds (2012 : Darmstadt, Germany) DRNTU::Engineering::Electrical and electronic engineering Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence level recognition algorithm, where the thresholds were used to identify different levels of the valence dimension of the human emotion. The algorithm was tested by using the EEG data labeled with valence levels. The algorithm could identify valence levels continuously. The algorithm was tested with the experiment data and with the benchmark affective EEG database DEAP where up to 9 levels of valence dimension with high/low dominance were recognized. Then, the algorithm was applied to recognize 16 emotions defined by high/low arousal, high/low dominance and 4 levels of valence. At least 14 electrodes should be used to get the better accuracy. The proposed algorithm could be implemented in different real-time applications such as emotional avatar and E-learning systems. 2013-08-01T02:13:37Z 2019-12-06T15:50:55Z 2013-08-01T02:13:37Z 2019-12-06T15:50:55Z 2012 2012 Conference Paper Liu, Y.,& Sourina, O. (2012). EEG-based Valence Level Recognition for Real-Time Applications. 2012 International Conference on Cyberworlds, 53-60. https://hdl.handle.net/10356/84767 http://hdl.handle.net/10220/12706 10.1109/CW.2012.15 en |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Liu, Yisi. Sourina, Olga. EEG-based valence level recognition for real-time applications |
| title | EEG-based valence level recognition for real-time applications |
| title_full | EEG-based valence level recognition for real-time applications |
| title_fullStr | EEG-based valence level recognition for real-time applications |
| title_full_unstemmed | EEG-based valence level recognition for real-time applications |
| title_short | EEG-based valence level recognition for real-time applications |
| title_sort | eeg based valence level recognition for real time applications |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/84767 http://hdl.handle.net/10220/12706 |
| work_keys_str_mv | AT liuyisi eegbasedvalencelevelrecognitionforrealtimeapplications AT sourinaolga eegbasedvalencelevelrecognitionforrealtimeapplications |