190 citations · 459 across the 9 of their papers we have counts for
4 papers · 1 filter
MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification
Phairot Autthasan, Rattanaphon Chaisaen, Thapanun Sudhawiyangkul +7
Advances in the motor imagery (MI)-based brain-computer interfaces (BCIs) allow control of several applications by decoding neurophysiological phenomena, which are usually recorded…
Drowsiness Detection for Office-based Workload with Mouse and Keyboard Data
Sanurak Natnithikarat, Sirakorn Lamyai, Pitshaporn Leelaarporn +4
Non-invasive devices involved in the detection of drowsiness generally include infrared camera and Electroencephalography (EEG), of which sometimes are constrained in an actual rea…
A Single-Channel Consumer-Grade EEG Device for Brain-Computer Interface: Enhancing Detection of SSVEP and Its Amplitude Modulation
Phairot Autthasan, Xiangqian Du, Jetsada Arnin +6
Brain-Computer interfaces (BCIs) play a significant role in easing neuromuscular patients on controlling computers and prosthetics. Due to their high signal-to-noise ratio, steady-…
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…