Adaptive feature extraction of four-class motor imagery EEG based on best basis of wavelet packet and CSP

2011 ◽  
Author(s):  
Ming-Ai Li ◽  
Lin Lin ◽  
Yang Jin-Fu
Keyword(s):  
Feature Extraction ◽  
Motor Imagery ◽  
Wavelet Packet ◽  
Adaptive Feature Extraction

Motor Imagery EEG Recognition Based on WPD-CSP and KF-SVM in Brain Computer Interfaces

2014 ◽  
Vol 556-562 ◽  
pp. 2829-2833 ◽  
Author(s):  
Bang Hua Yang ◽  
Ting Wu ◽  
Qian Wang ◽  
Zhi Jun Han
Keyword(s):  
Feature Extraction ◽  
Motor Imagery ◽  
Kernel Function ◽  
Feature Vector ◽  
Wavelet Packet ◽  
Support Vector ◽  
Wavelet Packet Decomposition ◽  
Brain Computer Interfaces ◽  
Recognition Method ◽  
Computer Interfaces

A recognition method based on Wavelet Packet Decomposition - Common Spatial Patterns (WPD-CSP) and Kernel Fisher Support Vector Machine (KF-SVM) is developed and used for EEG recognition in motor imagery brain–computer interfaces (BCIs). The WPD-CSP is used for feature extraction and KF-SVM is used for classification. The presented recognition method includes the following steps: (1) some important EEG channels are selected. The 'haar' wavelet basis is used to take wavelet packet decomposition. And some decomposed sub-bands related with motor imagery for each EEG channel are reconstructed to obtain the relevant frequency information. (2) A six-dimensional feature vector is obtained by the CSP feature extraction to the reconstructed signal. And then the within-class scatter is calculated based on the feature vector. (3) The scatter is added into the radical basis function to construct a new kernel function. The obtained new kernel is integrated into the SVM to act as its kernel function. To evaluate effectiveness of the proposed WPD-CSP + KF-SVM method, the data from the 2008 international BCI competition are processed. A preliminary result shows that the proposed classification algorithm can well recognize EEG data and improve the EEG recognition accuracy in motor imagery BCIs.

scholarly journals Adaptive feature extraction in EEG-based motor imagery BCI: tracking mental fatigue

2020 ◽  
Vol 17 (1) ◽  
pp. 016020
Author(s):  
Upasana Talukdar ◽  
Shyamanta M Hazarika ◽  
John Q Gan
Keyword(s):  
Feature Extraction ◽  
Motor Imagery ◽  
Mental Fatigue ◽  
Adaptive Feature Extraction

scholarly journals Adaptive Feature Extraction of Motor Imagery EEG with Optimal Wavelet Packets and SE-Isomap

2017 ◽  
Vol 7 (4) ◽  
pp. 390 ◽  
Author(s):  
Ming-ai Li ◽  
Wei Zhu ◽  
Hai-na Liu ◽  
Jin-fu Yang
Keyword(s):  
Feature Extraction ◽  
Motor Imagery ◽  
Wavelet Packets ◽  
Adaptive Feature Extraction
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