EEG Based Emotion Prediction with Neural Network Models
The term "emotion" refers to an individual's response to an event, person, or condition. In recent years, there has been an increase in the number of papers that have studied emotion estimation. In this study, a dataset based on three different emotions, utilized to classify feelings...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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University North
2022-01-01
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| Series: | Tehnički Glasnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/410701 |
| _version_ | 1797206680308547584 |
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| author | F. Kebire Bardak M. Nuri Seyman Feyzullah Temurtaş |
| author_facet | F. Kebire Bardak M. Nuri Seyman Feyzullah Temurtaş |
| author_sort | F. Kebire Bardak |
| collection | DOAJ |
| description | The term "emotion" refers to an individual's response to an event, person, or condition. In recent years, there has been an increase in the number of papers that have studied emotion estimation. In this study, a dataset based on three different emotions, utilized to classify feelings using EEG brainwaves, has been analysed. In the dataset, six film clips have been used to elicit positive and negative emotions from a male and a female. However, there has not been a trigger to elicit a neutral mood. Various classification approaches have been used to classify the dataset, including MLP, SVM, PNN, KNN, and decision tree methods. The Bagged Tree technique which is utilized for the first time has been achieved a 98.60 percent success rate in this study, according to the researchers. In addition, the dataset has been classified using the PNN approach, and achieved a success rate of 94.32 percent. |
| first_indexed | 2024-04-24T09:10:52Z |
| format | Article |
| id | doaj.art-c992549199fe4c9cbba6b76e7b19bd83 |
| institution | Directory Open Access Journal |
| issn | 1846-6168 1848-5588 |
| language | English |
| last_indexed | 2024-04-24T09:10:52Z |
| publishDate | 2022-01-01 |
| publisher | University North |
| record_format | Article |
| series | Tehnički Glasnik |
| spelling | doaj.art-c992549199fe4c9cbba6b76e7b19bd832024-04-15T17:58:02ZengUniversity NorthTehnički Glasnik1846-61681848-55882022-01-0116449750210.31803/tg-20220330064309EEG Based Emotion Prediction with Neural Network ModelsF. Kebire Bardak0M. Nuri Seyman1Feyzullah Temurtaş2Department of Electrical and Electronics Engineering, Bandırma Onyedi Eylül University, Balikesir, Bandirma, TurkeyDepartment of Electrical and Electronics Engineering, Bandırma Onyedi Eylül University, Balikesir, Bandirma, Turkey(1) Department of Electrical and Electronics Engineering, Bandırma Onyedi Eylül University, Balikesir, Bandirma, Turkey / (2) AINTELIA Artificial Intelligence Technologies Company, 16240, Bursa, TurkeyThe term "emotion" refers to an individual's response to an event, person, or condition. In recent years, there has been an increase in the number of papers that have studied emotion estimation. In this study, a dataset based on three different emotions, utilized to classify feelings using EEG brainwaves, has been analysed. In the dataset, six film clips have been used to elicit positive and negative emotions from a male and a female. However, there has not been a trigger to elicit a neutral mood. Various classification approaches have been used to classify the dataset, including MLP, SVM, PNN, KNN, and decision tree methods. The Bagged Tree technique which is utilized for the first time has been achieved a 98.60 percent success rate in this study, according to the researchers. In addition, the dataset has been classified using the PNN approach, and achieved a success rate of 94.32 percent.https://hrcak.srce.hr/file/410701AdaBoostbagged treeEEG signalsemotion predictionmulti-layer perceptronprobabilistic neural networks |
| spellingShingle | F. Kebire Bardak M. Nuri Seyman Feyzullah Temurtaş EEG Based Emotion Prediction with Neural Network Models Tehnički Glasnik AdaBoost bagged tree EEG signals emotion prediction multi-layer perceptron probabilistic neural networks |
| title | EEG Based Emotion Prediction with Neural Network Models |
| title_full | EEG Based Emotion Prediction with Neural Network Models |
| title_fullStr | EEG Based Emotion Prediction with Neural Network Models |
| title_full_unstemmed | EEG Based Emotion Prediction with Neural Network Models |
| title_short | EEG Based Emotion Prediction with Neural Network Models |
| title_sort | eeg based emotion prediction with neural network models |
| topic | AdaBoost bagged tree EEG signals emotion prediction multi-layer perceptron probabilistic neural networks |
| url | https://hrcak.srce.hr/file/410701 |
| work_keys_str_mv | AT fkebirebardak eegbasedemotionpredictionwithneuralnetworkmodels AT mnuriseyman eegbasedemotionpredictionwithneuralnetworkmodels AT feyzullahtemurtas eegbasedemotionpredictionwithneuralnetworkmodels |