Time-Variant Linear Discriminant Analysis Improves Hand Gesture and Finger Movement Decoding for Invasive Brain-Computer Interfaces

Time-Variant Linear Discriminant Analysis Improves Hand Gesture and Finger Movement Decoding for Invasive Brain-Computer Interfaces

Invasive brain-computer interfaces yield remarkable performance in a multitude of applications. For classification experiments, high-gamma bandpower features and linear discriminant analysis (LDA) are commonly used due to simplicity and robustness. However, LDA is inherently static and not suited to...

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Bibliographic Details
Main Authors: Johannes Gruenwald, Andrei Znobishchev, Christoph Kapeller, Kyousuke Kamada, Josef Scharinger, Christoph Guger
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-09-01
Series:Frontiers in Neuroscience
Subjects:
brain-computer interface
electrocorticography
movement decoding
linear discriminant analysis
spectral whitening
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00901/full

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https://www.frontiersin.org/article/10.3389/fnins.2019.00901/full

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