Motor Imagery EEG Classification Based on Multi-Domain Feature Rotation and Stacking Ensemble

Motor Imagery EEG Classification Based on Multi-Domain Feature Rotation and Stacking Ensemble

Background: Decoding motor intentions from electroencephalogram (EEG) signals is a critical component of motor imagery-based brain–computer interface (MI–BCIs). In traditional EEG signal classification, effectively utilizing the valuable information contained within the electroencephalogram is cruci...

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Bibliographic Details
Main Authors: Xianglong Zhu, Ming Meng, Zewen Yan, Zhizeng Luo
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Brain Sciences
Subjects:
electroencephalogram
motor imagery
stacking ensemble
multi-domain features
rotation transform
Online Access:https://www.mdpi.com/2076-3425/15/1/50
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