Classification of 4-class Motor Imagery EEG Data with Common Sparse Spectral Spatial Pattern Method

Date

2009-01-01

Author

Akinci, Berna
Gençer, Nevzat Güneri

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Brain Computer Interface aims to provide a communication system with external media via thougths. For this purpose, brain signals are acquired from the scalp by EEG device and processed for characterization. In this work, the classification of movement imagery EEG data has been studied for left hand, right hand, foot and tongue movement imagination cases. Common Spatial Patterns (CSP) method and temporal filters have been used in classification and Common Sparse Spectral Spatial Patterns (CSSSP) method has been tried on 4-class motor imagery data in order to improve the accuracy for classification.

Subject Keywords

Brain Computer Interface, Common Spatial Patterns, EEG, motor imagery, FILTERS

URI

https://hdl.handle.net/11511/100935

DOI

https://doi.org/10.1109/biyomut.2009.5130261

Conference Name

14th National Biomedical Engineering Meeting

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

B. Akinci and N. G. Gençer, “Classification of 4-class Motor Imagery EEG Data with Common Sparse Spectral Spatial Pattern Method,” presented at the 14th National Biomedical Engineering Meeting, İzmir, Türkiye, 2009, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100935.