Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review
Despite its short history, the use of Riemannian geometry in brain-computer interface (BCI)
decoding is currently attracting increasing attention, due to accumulating documentation of …
decoding is currently attracting increasing attention, due to accumulating documentation of …
Motor imagery EEG classification based on decision tree framework and Riemannian geometry
S Guan, K Zhao, S Yang - Computational intelligence and …, 2019 - Wiley Online Library
This paper proposes a novel classification framework and a novel data reduction method to
distinguish multiclass motor imagery (MI) electroencephalography (EEG) for brain computer …
distinguish multiclass motor imagery (MI) electroencephalography (EEG) for brain computer …
[PDF][PDF] A Complete Survey on Common Spatial Pattern Techniques in Motor Imagery BCI
S Akuthota, KR Kumar, JR Chander - Journal of Scientific and …, 2023 - academia.edu
Background: Brain-computer interfaces that use motor imagery hold promise for direct
communication and control through brain signals. Common Spatial Pattern (CSP) …
communication and control through brain signals. Common Spatial Pattern (CSP) …
A separability marker based on high-dimensional statistics for classification confidence assessment
NTH Gayraud, N Foy, M Clerc - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
This work provides a theoretical analysis framework for features that belong to the high
dimensional Riemannian manifold of symmetric positive definite matrices. In non-invasive …
dimensional Riemannian manifold of symmetric positive definite matrices. In non-invasive …