Classifications of Motor Imagery Tasks in Brain Computer Interface Using Linear Discriminant Analysis
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2014, Vol 3, Issue 7
Abstract
In this paper, we address a method for motor imagery feature extraction for brain computer interface (BCI). The wavelet coefficients were used to extract the features from the motor imagery EEG and the linear discriminant analysis was utilized to classify the pattern of left or right hand imagery movement and rest. The performance of the proposed method was evaluated using EEG data recorded by us, with 8 g.tec active electrodes by means of g.MOBIlab+ module. The maximum accuracy of classification is 91%.
Authors and Affiliations
Roxana Aldea, Monica Fira
Keywords
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- EP ID EP131744
- DOI 10.14569/IJARAI.2014.030702
- Views 158
- Downloads 0
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