A causal viewpoint on motor-imagery brainwave decoding
File(s)
Published version
Author(s)
Barmpas, Konstantinos
Panagakis, Ioannis
Adamos, Dimitrios
Laskaris, Nikolaos
Zafeiriou, Stefanos
Type
Conference Paper
Abstract
In this work, we employ causal reasoning to breakdown and analyze important challenges of the decoding of Motor-Imagery (MI) electroencephalography (EEG) signals. Furthermore, we present a framework consisting of dynamic convolutions, that address one of the issues that arises through this causal investigation, namely the subject distribution shift (or inter-subject variability). Using a publicly available MI dataset, we demonstrate increased cross-subject performance in two different MI tasks for four well-established deep architectures.
Date Issued
2023-05-05
Date Acceptance
2022-04-29
Citation
2023
Publisher
OpenReview.net
Copyright Statement
© 2022 The Author(s).
Source
ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality
Publication Status
Published
Start Date
2022-04-29
Coverage Spatial
Virtual
Date Publish Online
2022-03-25