Decision tree structure based classification of EEG signals recorded during two dimensional cursor movement imagery

AYDEMİR Ö., KAYIKÇIOĞLU T.

JOURNAL OF NEUROSCIENCE METHODS, cilt.229, ss.68-75, 2014 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 229
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1016/j.jneumeth.2014.04.007
  • Dergi Adı: JOURNAL OF NEUROSCIENCE METHODS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.68-75
  • Anahtar Kelimeler: EEG, Brain computer interface, Feature extraction, Classification, Computer cursor movement imagery, BRAIN-COMPUTER-INTERFACE, COMMON SPATIAL-PATTERNS, BCI COMPETITION 2003, MOTOR IMAGERY, WAVELET TRANSFORM, PERFORMANCE, VECTORS
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Background: Input signals of an EEG based brain computer interface (BCI) system are naturally non-stationary, have poor signal to noise ratio, depend on physical or mental tasks and are contaminated with various artifacts such as external electromagnetic waves, electromyogram and electrooculogram. All these disadvantages have motivated researchers to substantially improve speed and accuracy of all components of the communication system between brain and a BCI output device.