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eess.SP2018
Towards Asynchronous Motor Imagery-Based Brain-Computer Interfaces: a joint training scheme using deep learning
Patcharin Cheng, Phairot Autthasan, Boriwat Pijarana +2
In this paper, the deep learning (DL) approach is applied to a joint training scheme for asynchronous motor imagery-based Brain-Computer Interface (BCI). The proposed DL approach i…
eess.SP2018
Universal Joint Feature Extraction for P300 EEG Classification using Multi-task Autoencoder
Apiwat Ditthapron, Nannapas Banluesombatkul, Sombat Ketrat +2
The process of recording Electroencephalography (EEG) signals is onerous and requires massive storage to store signals at an applicable frequency rate. In this work, we propose the…
eess.SP2018
Affective EEG-Based Person Identification Using the Deep Learning Approach
Theerawit Wilaiprasitporn, Apiwat Ditthapron, Karis Matchaparn +3
Electroencephalography (EEG) is another mode for performing Person Identification (PI). Due to the nature of the EEG signals, EEG-based PI is typically done while the person is per…