NDLI: Using Multiresolution Space-Time-Frequency Features for the Classification Motor Imagery Eeg Recordings in a Brain Computer Interface Task

Content Provider	IEEE Xplore Digital Library
Author	Firat, I.N. Arica, S. Tewfik, A.H.
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Minnesota Univ., Minneapolis, MN (Firat, I.N.)
Abstract	We introduce an adaptive space time frequency analysis to extract and classify subject specific brain oscillations induced by motor imagery in a brain computer interface task. The proposed method requires no prior knowledge of the reactive frequency bands, their temporal behavior or cortical locations. By using a modified local discriminant base algorithm (flexible LDB), our procedure calculates an arbitrary time-frequency segmentation of the given multichannel brain activity recordings to extract subject specific ERD and ERS patterns. The extracted time-frequency features are processed by principal component analysis to reduce the feature set which is highly correlated due to volume conduction and the neighbor cortical regions. The reduced feature set is then fed into a linear discriminant analysis for classification. We describe experimental results for 9 subjects that show the superior performance of the proposed method. The classification accuracy for the subjects varied between 76.4% and 96.8% and the average classification accuracy was 84.9%.
Starting Page	359
Ending Page	364
File Size	5747157
Page Count	6
File Format	PDF
ISBN	1424406560
ISSN	15512541
DOI	10.1109/MLSP.2006.275575
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-09-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Electroencephalography Brain computer interfaces Time frequency analysis Principal component analysis Linear discriminant analysis Neuroscience Electronic mail Image segmentation Disk recording
Content Type	Text
Resource Type	Article

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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
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A Space-time-Frequency Analysis Approach for the Classification Motor Imagery EEG Recordings in a Brain Computer Interface Task

Using multiresolution space-time-frequency features for the classification motor imagery eeg recordings in a brain computer interface task.

Classification of Motor Imagery EEG recordings with Subject Specific Time-Frequency Patterns

The feature extraction of motor imagery EEG based on the time-frequency correction

A space-time-frequency analysis approach for the classification motor imagery eeg recordings in a brain computer interface task.

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Analysis of correlated EEG activity during motor imagery for brain-computer interfaces

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Using Multiresolution Space-Time-Frequency Features for the Classification Motor Imagery Eeg Recordings in a Brain Computer Interface Task

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