NDLI: Feature extraction method of motor imagery EEG based on DTCWT sample entropy

Content Provider	IEEE Xplore Digital Library
Author	Meng Ming Lu Shaona Man Haitao Ma Yuliang Gao Yunyuan
Copyright Year	2015
Description	Author affiliation: Inst. of Intell. Control & Robot, Hangzhou Dianzi Univ., Hangzhou, China (Meng Ming; Lu Shaona; Man Haitao; Ma Yuliang; Gao Yunyuan)
Abstract	Aiming at the applications of Brain Computer Interface (BCI) based on motor imagery EEG, this paper presents a feature extraction method combining Dual-Tree Complex Wavelet Transform (DTCWT) and sample entropy. Firstly, the motor imagery EEG signals are decomposed by DTCWT. Then, the rhythm waves corresponding to the event-related desynchronization (ERD)/event-related synchronization (ERS) phenomenon are extracted and reconstructed. Finally, the features are extracted from the rhythm signal using sample entropy. The Datasets1 of BCI Competition IV, including motor imagery EEG data of left hand, right hand and foot, is used to verify the proposed method. A Support Vector Machine (SVM) classifier is introduced in the classification experiments. The average classification accuracy rate of four subjects is 87.25% in the experiments with the Datasets1 of BCI Competition IV. The results show that the feature extraction method has more obvious separability and practicability.
Starting Page	3964
Ending Page	3968
File Size	453054
Page Count	5
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260250
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Wavelet transforms Sample Entropy DTCWT EEG Feature extraction Rhythm Electroencephalography Entropy SVM Image reconstruction
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Motor imagery EEG signal classification scheme based on wavelet domain statistical features

Research on classification method of wavelet entropy and Fuzzy Neural Networks for motor imagery EEG

A combined feature extraction method for left-right hand motor imagery in BCI

Brain-robot interface: Distinguishing left and right hand EEG signals through SVM

Identification of motor imagery movements from EEG signals using Dual Tree Complex Wavelet Transform

Dual tree complex wavelet transform domain based motor imagery movements classification scheme from EEG signals

Feature extraction and classification of EEG for imaging left-right hands movement

Discrimination of EEG related to motor imagery by combined wavelet energy feature with phase synchronization feature

Motor Imagery BCI Research Based on Sample Entropy and SVM

Feature extraction method of motor imagery EEG based on DTCWT sample entropy

Similar Documents

Motor imagery EEG signal classification scheme based on wavelet domain statistical features

Research on classification method of wavelet entropy and Fuzzy Neural Networks for motor imagery EEG

A combined feature extraction method for left-right hand motor imagery in BCI

Brain-robot interface: Distinguishing left and right hand EEG signals through SVM

Identification of motor imagery movements from EEG signals using Dual Tree Complex Wavelet Transform

Dual tree complex wavelet transform domain based motor imagery movements classification scheme from EEG signals

Feature extraction and classification of EEG for imaging left-right hands movement

Discrimination of EEG related to motor imagery by combined wavelet energy feature with phase synchronization feature

Motor Imagery BCI Research Based on Sample Entropy and SVM

Feature extraction method of motor imagery EEG based on DTCWT sample entropy