Enhance decoding of lower limb motor imagery‐electroencephalography patterns by Riemannian clustering

Enhance decoding of lower limb motor imagery‐electroencephalography patterns by Riemannian clustering

Abstract Brain‐Computer Interface (BCI) based on motor imagery (MI) has attracted great interest as a new rehabilitation method for stroke. Riemannian geometry‐based classification algorithms are widely used in MI‐BCI due to their strong robustness and generalization capabilities. However, the clust...

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Bibliographic Details
Main Authors: Xinwei Sun, Tuo Liu, Kun Wang, Lincong Pan, Lin Meng, Xinmin Ding, Weibo Yi, Minpeng Xu, Dong Ming
Format: Article
Language:English
Published: Wiley-VCH 2025-07-01
Series:Interdisciplinary Medicine
Subjects:
brain‐computer interface (BCI)
motor imagery (MI)
Riemannian clustering
subcluster
Online Access:https://doi.org/10.1002/INMD.20250003
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