ThinICA-CSP algorithm for discrimination of multiclass motor imagery movements
| Autor: | E R Rajkumar, Sergio Cruces, Deepa Beeta Thiyam |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Speedup
business.industry Computer science 0206 medical engineering Pattern recognition 02 engineering and technology Filter (signal processing) 020601 biomedical engineering 03 medical and health sciences Matrix (mathematics) ComputingMethodologies_PATTERNRECOGNITION 0302 clinical medicine Motor imagery Artificial intelligence business Joint (audio engineering) Algorithm 030217 neurology & neurosurgery |
| Zdroj: | 2016 IEEE Region 10 Conference (TENCON). |
| DOI: | 10.1109/tencon.2016.7848480 |
| Popis: | This paper presents a ThinICA-CSP1 algorithm for discrimination of multiclass motor imagery (MI) movements for Brain Computer Interfacing (BCI) applications. This algorithm performs a joint approximate diagonalization of the second and higher order statistics of the observations with the aim of identifying the relevant independent components of the EEG signals and their corresponding spatial filters. In order to speed up the convergence, the algorithm is initialized from the multiclass Common Spatial Pattern (CSP) filter matrix. This helps the ICA algorithm to find the closest solution to the problem. The algorithm was tested on BCI competition IV dataset 2a and the obtained performance was compared with two existing methods. An improvement in classification performance is observed using the ThinICA-CSP algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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