A Novel Small-Data Based Approach for Decoding Yes/No-Decisions of Locked-In Patients Using Generative Adversarial Networks

A Novel Small-Data Based Approach for Decoding Yes/No-Decisions of Locked-In Patients Using Generative Adversarial Networks

We demonstrate how to use generative adversarial networks to improve the small data problem when training brain-computer-interfaces. The new approach is based on finely graded frequency bands, which are extracted from motor imagery electroencephalography data by using power spectral density method t...

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Bibliographic Details
Main Authors: Pascal Penava, Ricardo Buettner
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Brain-computer-interface
decision prediction
generative adversarial networks
motor imagery tasks
electroencephalography
machine learning
Online Access:https://ieeexplore.ieee.org/document/10290875/

Internet

https://ieeexplore.ieee.org/document/10290875/

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