Deep Adversarial Domain Adaptation With Few-Shot Learning for Motor-Imagery Brain-Computer Interface

Deep Adversarial Domain Adaptation With Few-Shot Learning for Motor-Imagery Brain-Computer Interface

Electroencephalography (EEG) is the most prevalent signal acquisition technique for brain-computer interface (BCI). However, the statistical distribution of EEG data varies across subjects and sessions, resulting in poor generalization of the domain-specific classifier. Although the collection of a...

Full description

Bibliographic Details
Main Authors: Chatrin Phunruangsakao, David Achanccaray, Mitsuhiro Hayashibe
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Brain-computer interface
motor imagery
few-shot learning
domain adaptation
representation learning
Online Access:https://ieeexplore.ieee.org/document/9782441/

Similar Items

Similar Items