@InProceedings{8553382,
  author = {F. Altindis and B. Yilmaz and S. Borisenok and K. Icoz},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Use of Topological Data Analysis in Motor Intention Based Brain-Computer Interfaces},
  year = {2018},
  pages = {1695-1699},
  abstract = {This study aims to investigate the use of topological data analysis in electroencephalography (EEG) based on brain-computer interface (BCI) 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 JPlex 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.},
  keywords = {brain-computer interfaces;data analysis;electroencephalography;feature extraction;medical signal processing;nearest neighbour methods;neurophysiology;signal classification;brain-computer interface applications;topological feature extraction;Betti numbers;motor activity tasks;motor intention based brain-computer interfaces;electroencephalography;data point clouds;real-time simulation scenario;JPlex toolbox;k-NN classifier;hand motor intentions;topological structure;motor cortex area;EEG signals;topological data analysis;Electroencephalography;Three-dimensional displays;Data analysis;Electrodes;Signal processing;Feature extraction;Shape;EEG;brain-computer interfaces;topological data analysis;motor intention waves;JPlex},
  doi = {10.23919/EUSIPCO.2018.8553382},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438034.pdf},
}

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Altindis and B. Yilmaz and S. Borisenok and K. Icoz},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Use of Topological Data Analysis in Motor Intention Based Brain-Computer Interfaces},\n year = {2018},\n pages = {1695-1699},\n abstract = {This study aims to investigate the use of topological data analysis in electroencephalography (EEG) based on brain-computer interface (BCI) 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 JPlex 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. 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