Riemannian Channel Selection for BCI With Between-Session Non-Stationarity Reduction Capabilities

Riemannian Channel Selection for BCI With Between-Session Non-Stationarity Reduction Capabilities

Objective: Between-session non-stationarity is a major challenge of current Brain-Computer Interfaces (BCIs) that affects system performance. In this paper, we investigate the use of channel selection for reducing between-session non-stationarity with Riemannian BCI classifiers. We use the Riemannia...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Khadijeh Sadatnejad, Fabien Lotte
Format: Artikel
Sprache:English
Veröffentlicht: IEEE 2022-01-01
Schriftenreihe:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Schlagworte:
Brain-computer interfaces
EEG
Riemannian manifold
channel selection
non-stationarity
Online Zugang:https://ieeexplore.ieee.org/document/9757884/

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https://ieeexplore.ieee.org/document/9757884/

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