Mining and Extracting Emotional Information from Human-Based EEG: An Overview
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CHAKRAVORTY S K (EDITOR) PRODUCTIVITYSummary: Emotion plays a vital role in our lives such as attention, memory and decision making and communication. Emotion recognition is a step towards aiding people such as in care taking and designing brain computer interfaces. Nowadays, automatic emotion recognition is one of the most popular research topics in the fields of computer vision, speech recognition, brain-machine interface, and computational neuroscience. Recognizing emotions from EEG (Electroencephalogram) signals permits us to evaluate the internal condition of the subject, which is viewed as an important factor in HCI (Human Computer Interaction). One of the most important things in improving accuracy of emotion recognition is based upon choosing the Good Artifact Removal algorithm, Feature extraction, Feature selection method and Classification algorithms. This paper reviews EEG emotion recognition
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Main Library | Vol 59, No 4/ 55510181JA3 (Browse shelf(Opens below)) | Available | 55510181JA3 | |||||
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Main Library On Display | JOURNAL/OPERATION/Vol 59, No 4/55510181 (Browse shelf(Opens below)) | Vol 59, No 4 (01/01/2019) | Not for loan | January - March, 2019 | 55510181 |
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Emotion plays a vital role in our lives such as attention, memory and decision making and communication. Emotion recognition is a step towards aiding people such as in care taking and designing brain computer interfaces. Nowadays, automatic emotion recognition is one of the most popular research topics in the fields of computer vision, speech recognition, brain-machine interface, and computational neuroscience. Recognizing emotions from EEG (Electroencephalogram) signals permits us to evaluate the internal condition of the subject, which is viewed as an important factor in HCI (Human Computer Interaction). One of the most important things in improving accuracy of emotion recognition is based upon choosing the Good Artifact Removal algorithm, Feature extraction, Feature selection method and Classification algorithms. This paper reviews EEG emotion recognition
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