Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Electroencephalography (EEG) is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG) not only has a close correlation with the human imagination and movement intention but also contains a large amount of physiological...

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Bibliographic Details
Main Authors: Ming-ai Li, Hai-na Liu, Wei Zhu, Jin-fu Yang
Format: Article
Language:English
Published: MDPI AG 2017-01-01
Series:Applied Sciences
Subjects:
motor imagery electroencephalography
feature extraction
multiscale fuzzy entropy
independent optimization of parameters
complexity
t-test
Online Access:http://www.mdpi.com/2076-3417/7/1/92

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http://www.mdpi.com/2076-3417/7/1/92

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