Decimation Filter with Common Spatial Pattern and Fishers Discriminant Analysis for Motor Imagery Classification

Kumar, Shiu and Sharma, Ronesh and Sharma, Alokanand and Tsunoda, T. (2016) Decimation Filter with Common Spatial Pattern and Fishers Discriminant Analysis for Motor Imagery Classification. [Conference Proceedings]

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Abstract

Brain Computer Interface (BCI) system converts thoughts into commands for driving external device with Electroencephalography (EEG). This paper presents the use of decimation filters for filtering the EEG signal. Common Spatial Pattern (CSP) technique is used to transform the filtered signal to a new time series in order to have optimal variance for the discrimination of different tasks. Fishers Discriminant Analysis (FDA) is applied to the CSP features and the FDA scores are fed to a Support Vector Machine (SVM) classifier. The method is evaluated on BCI Competition III Dataset IVa and compared with other related state-of-the-art approaches. The results show that our method outperforms all other approaches in terms of average classification error rate. Compared to best performing method that uses only CSP features, the results obtained in this research offer on average a reduction of 1.07% in the classification error rate.

Item Type:	Conference Proceedings
Subjects:	Q Science > Q Science (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User:	Fulori Nainoca - Waqairagata
Date Deposited:	10 Mar 2017 00:31
Last Modified:	15 Jun 2018 03:44
URI:	http://repository.usp.ac.fj/id/eprint/9666

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