EEG emotion detection review
- ,
- Mohamed Ahmed Abdullah
- Sudan University of Science & Technology
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewPublication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPublication milestones
- Published - 2018
Publication status
Published - 2018
Publisher
IEEE, United StatesISBN (Print)
978-1-5386-1400-6ISBN (Electronic)
978-1-5386-1399-3Publication IDs
- Scopus: 85051022091
Host publication title
2018 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)Abstract
EEG (Electroencephalography) allows to elicit the mental state of the user, which in turn reveals the user emotion, which is an important factor in HMI (Human Machine Interaction). Researchers across the globe are developing new techniques to increase the EEG accuracy by using different signal processing, statistics, and machine learning techniques in this work we will discuss the most common techniques that can yield to better results, along with discussing the common experiment steps to classify the emotion, starting from collecting the signal, and extracting the features and select the best feature to classify the emotions. Along with highlighting some standing problems in field and potential growth areas.
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