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Classification of ECoG Motor Image using Fusion Technique

by Aswinseshadri K, Thulasi Bai V
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 9
Year of Publication: 2014
Authors: Aswinseshadri K, Thulasi Bai V
10.5120/17551-8147

Aswinseshadri K, Thulasi Bai V . Classification of ECoG Motor Image using Fusion Technique. International Journal of Computer Applications. 100, 9 ( August 2014), 6-11. DOI=10.5120/17551-8147

@article{ 10.5120/17551-8147,
author = { Aswinseshadri K, Thulasi Bai V },
title = { Classification of ECoG Motor Image using Fusion Technique },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 9 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number9/17551-8147/ },
doi = { 10.5120/17551-8147 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:30.382104+05:30
%A Aswinseshadri K
%A Thulasi Bai V
%T Classification of ECoG Motor Image using Fusion Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 9
%P 6-11
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Brain-Computer Interfaces (BCIs) ensure non-muscular communication between a user and external device by using brain activity. Currently, BCIs were applied in the medical field to increase quality of life of patients suffering from neuromuscular disorders. Most BCI systems use scalp recorded electroencephalographic activity, while Electrocorticography (ECoG) is a minimally-invasive alternative to Electroencephalogram (EEG), which ensures higher and superior signal characteristics enabling rapid user training and quicker communication. This paper presents a BCI system; ECoG signals are pre-processed and features are extracted from using Wavelet Packet Tree and Common Spatial Pattern. The extracted features are fused using Median Absolute Deviation (MAD) to improve the discrimination power of the feature vector. BCI Competition III, Data Set I having ECoG recordings motor imagery is used in investigation to evaluate the presented methodology.

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Index Terms

Computer Science
Information Sciences

Keywords

Brain–computer interface (BCI) Electrocorticography (ECoG) Wavelet Packet Tree Common Spatial Pattern Motor Imagery

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