Enhancement of Time-Frequency Energy for the Classification of Motor Imagery Electroencephalogram Based on an Improved FitzHugh–Nagumo Neuron System

Enhancement of Time-Frequency Energy for the Classification of Motor Imagery Electroencephalogram Based on an Improved FitzHugh–Nagumo Neuron System

Brain-computer interface (BCI) based on motor imagery (MI) electroencephalogram (EEG) has become an essential way for rehabilitation, because of the activation and interaction of motor neurons between the brain and rehabilitation devices in recent years. However, due to the discrepancies between ind...

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Bibliographic Details
Main Authors: Ruiquan Chen, Guanghua Xu, Yaguang Jia, Cheng Zhou, Zhao Wang, Jinju Pei, Chengcheng Han, Yi Wang, Sicong Zhang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Motor imagery
brain-computer interface
FHN neuron system
time-frequency energy
Online Access:https://ieeexplore.ieee.org/document/9945982/

Internet

https://ieeexplore.ieee.org/document/9945982/

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