Analysis of Dimension Reduction by PCA and AdaBoost on Spelling Paradigm EEG Data

YILDIRIM A., HALICI U.

6th International Conference on Biomedical Engineering and Informatics (BMEI), Hangzhou, Çin, 16 - 18 Aralık 2013, ss.192-196 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/bmei.2013.6746932
  • Basıldığı Şehir: Hangzhou
  • Basıldığı Ülke: Çin
  • Sayfa Sayıları: ss.192-196
  • Anahtar Kelimeler: Brain Computer Interfaces, Spelling Paradigm, Principal Component Analysis, Adaboost, Support Vector Machine, BCI COMPETITION 2003, MENTAL PROSTHESIS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Spelling Paradigm is a BCI application which aims to construct words by finding letters using P300 signals recorded via channel electrodes attached to the diverse points of the scalp. In this study effects of dimension reduction using Principal Component Analysis (PCA) and AdaBoost methods on time domain characteristics of P300 evoked potentials in Spelling Paradigm are analyzed. Support Vector Machine (SVM) is used for classification.