A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces

The decoding of hand movement kinematics using non-invasive data acquisition techniques is a recent area of research in Brain Computer Interface (BCI). In this work, we use an Electroencephalography (EEG) based BCI to decode directional information from the brain data collected during an actual hand...

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Main Authors: Robinson, Neethu, Vinod, Achutavarrier Prasad, Guan, Cuntai, Ang, Kai Keng, Tee, Keng-Peng
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/98180
http://hdl.handle.net/10220/12422
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-981802022-07-01T01:45:34Z A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces Robinson, Neethu Vinod, Achutavarrier Prasad Guan, Cuntai Ang, Kai Keng Tee, Keng-Peng School of Computer Engineering International Joint Conference on Neural Networks (2012 : Brisbane, Australia) DRNTU::Engineering::Computer science and engineering The decoding of hand movement kinematics using non-invasive data acquisition techniques is a recent area of research in Brain Computer Interface (BCI). In this work, we use an Electroencephalography (EEG) based BCI to decode directional information from the brain data collected during an actual hand movement experiment. The objective is to find the discriminative features of movement related potential that can classify any two directions out of the four orthogonal directions in which subject performs right hand movement. The performance using Wavelet-Common Spatial Pattern (W-CSP) algorithm and its variations in terms of spatial regularization is studied and compared. The work further analyzes the involvement of frontal, parietal and motor regions in carrying movement kinematics information with the help of spatial plots given by CSP. The performance variability for different directions in various subjects is another important observation in our results. The work aims to provide a more refined movement control command set for BCIs by developing efficient techniques to decode the direction of movement. 2013-07-29T03:23:34Z 2019-12-06T19:51:49Z 2013-07-29T03:23:34Z 2019-12-06T19:51:49Z 2012 2012 Conference Paper Robinson, N., Vinod, A. P., Guan, C., Ang, K. K., & Tee, K. (2012). A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces. The 2012 International Joint Conference on Neural Networks (IJCNN). https://hdl.handle.net/10356/98180 http://hdl.handle.net/10220/12422 10.1109/IJCNN.2012.6252685 en © 2012 IEEE.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Robinson, Neethu
Vinod, Achutavarrier Prasad
Guan, Cuntai
Ang, Kai Keng
Tee, Keng-Peng
A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
description The decoding of hand movement kinematics using non-invasive data acquisition techniques is a recent area of research in Brain Computer Interface (BCI). In this work, we use an Electroencephalography (EEG) based BCI to decode directional information from the brain data collected during an actual hand movement experiment. The objective is to find the discriminative features of movement related potential that can classify any two directions out of the four orthogonal directions in which subject performs right hand movement. The performance using Wavelet-Common Spatial Pattern (W-CSP) algorithm and its variations in terms of spatial regularization is studied and compared. The work further analyzes the involvement of frontal, parietal and motor regions in carrying movement kinematics information with the help of spatial plots given by CSP. The performance variability for different directions in various subjects is another important observation in our results. The work aims to provide a more refined movement control command set for BCIs by developing efficient techniques to decode the direction of movement.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Robinson, Neethu
Vinod, Achutavarrier Prasad
Guan, Cuntai
Ang, Kai Keng
Tee, Keng-Peng
format Conference or Workshop Item
author Robinson, Neethu
Vinod, Achutavarrier Prasad
Guan, Cuntai
Ang, Kai Keng
Tee, Keng-Peng
author_sort Robinson, Neethu
title A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
title_short A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
title_full A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
title_fullStr A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
title_full_unstemmed A modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
title_sort modified wavelet-common spatial pattern method for decoding hand movement directions in brain computer interfaces
publishDate 2013
url https://hdl.handle.net/10356/98180
http://hdl.handle.net/10220/12422
_version_ 1738844899118153728