Pushing the boundaries of EEG-based emotion classification using consumer-grade wearable brain-computer interfacing devices and ensemble classifiers

• Main Authors: Jason Teo, Nazmi Sofian Suhaimi, James Mountstephens
• Format: Article
• Language: English
• Published: IJAST 2020
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: https://eprints.ums.edu.my/id/eprint/25709/1/Pushing%20the%20boundaries%20of%20EEG-based%20emotion%20classification%20using%20consumer-grade%20wearable%20brain-computer%20interfacing%20devices%20and%20ensemble%20classifiers.pdf; https://eprints.ums.edu.my/id/eprint/25709/

Emotion classification using features derived from electroencephalography (EEG) is currently one of the major research areas in big data. Although this area of research is not new, the current challenge is now to move from medical-grade EEG acquisition devices to consumer-grade EEG devices. The over...