Name
Abstract | ||
|---|---|---|
This study aims to investigate the use of topological data analysis in electroencephalography (EEG) based on brain computer interface (BC!) applications. Our study focused on extracting topological features of EEG signals obtained from the motor cortex area of the brain. EEG signals from 8 subjects were used for forming data point clouds with a real-time simulation scenario and then each cloud was processed with JPIex toolbox in order to find out corresponding Betti numbers. These numbers represent the topological structure of the point data cloud related to the persistent homologies, which differ for different motor activity tasks. The estimated Betti numbers has been used as features in k-NN classifier to discriminate left or right hand motor intentions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.23919/EUSIPCO.2018.8553382 | European Signal Processing Conference |
Keywords | Field | DocType |
EEG,brain-computer interfaces,topological data analysis,motor intention waves,JPlex | Topological data analysis,Betti number,Pattern recognition,Computer science,Brain–computer interface,Feature extraction,Motor cortex,Artificial intelligence,Point cloud,Classifier (linguistics),Electroencephalography | Conference |
ISSN | Citations | PageRank |
2076-1465 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fatih Altindis | 1 | 0 | 0.34 |
| Bülent Yilmaz | 2 | 4 | 2.48 |
| Sergey Borisenok | 3 | 0 | 0.34 |
| Kutay Icoz | 4 | 0 | 2.37 |