Sliding Window and Filterbank Utilization on Riemannian Geometry

ALTINDİŞ F., YILMAZ B.

16th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2022, Biarritz, Fransa, 8 - 12 Ağustos 2022 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/inista55318.2022.9894208
  • Basıldığı Şehir: Biarritz
  • Basıldığı Ülke: Fransa
  • Anahtar Kelimeler: Brain-Computer Interface, EEG, Riemannian Geometry, Tangent Space Mapping
  • Kayseri Üniversitesi Adresli: Hayır

Özet

© 2022 IEEE.Riemannian geometry-based signal processing approaches on EEG signals provides similar decoding performance compared to state-of-the-art methods. However, Riemannian geometry framework requires predefine EEG signal epoch that is to be used in the analysis. Sliding window approach that operates in Riemannian geometry proposed to enable use of EEG signals without constrained by the record length. Decoding performance of tangent space mapping was increased more than 6% in overall accuracy compared the previous study's results. Instead of using single band-pass filter, utilization of filterbank is proposed to increase decoding performance. Distance based Riemannian classifier's overall performance were increased by 5% compared to standard Riemannian geometry approach.