Research Article
Calculate the Quality Measures on Classification of Continuous EEG without Trial Structure EEG Dataset
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 147 - Issue 10 |
| Published: Aug 2016 |
| Authors: Mangesh J. Patil, Mukta G. Dhopeshwarkar, Pankaj A. Sathe |
10.5120/ijca2016911197
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Mangesh J. Patil, Mukta G. Dhopeshwarkar, Pankaj A. Sathe . Calculate the Quality Measures on Classification of Continuous EEG without Trial Structure EEG Dataset. International Journal of Computer Applications. 147, 10 (Aug 2016), 32-35. DOI=10.5120/ijca2016911197
@article{ 10.5120/ijca2016911197,
author = { Mangesh J. Patil,Mukta G. Dhopeshwarkar,Pankaj A. Sathe },
title = { Calculate the Quality Measures on Classification of Continuous EEG without Trial Structure EEG Dataset },
journal = { International Journal of Computer Applications },
year = { 2016 },
volume = { 147 },
number = { 10 },
pages = { 32-35 },
doi = { 10.5120/ijca2016911197 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2016
%A Mangesh J. Patil
%A Mukta G. Dhopeshwarkar
%A Pankaj A. Sathe
%T Calculate the Quality Measures on Classification of Continuous EEG without Trial Structure EEG Dataset%T
%J International Journal of Computer Applications
%V 147
%N 10
%P 32-35
%R 10.5120/ijca2016911197
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Quality measure is very significant method for signal processing. Using this processes we can evaluate the EEG signal to see whether the data are noisy or not. The quality measure is performed on BCI competition dataset, this dataset is having 14 EEG signal, 0.05-200 Hz, 1000 Hz sampling rates, 2 classes of 7 subjects. The resultant signal quality is verified by using different quality measures parameters like PSNR, MSE, MAXERR, and L2RAT. So it is conclude that quality of EEG signal has been enriched by using of median filter. Hence it is proved that the recognition rate is increases.
References
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