SuperLectures.com

STATIONARY COMMON SPATIAL PATTERNS: TOWARDS ROBUST CLASSIFICATION OF NON-STATIONARY EEG SIGNALS

Biosignal Processing

Full Paper at IEEE Xplore

Přednášející: Wojciech Wojcikiewicz, Autoři: Wojciech Wojcikiewicz, Carmen Vidaurre, Technical University of Berlin, Germany; Motoaki Kawanabe, Fraunhofer Institute FIRST, Germany

Brain-Computer Interfaces (BCIs) allow a user to control a computer application by brain activity as acquired, e.g., by EEG. A standard step in a BCI system is to project the EEG signals to a low-dimensional subspace using Common Spatial Patterns (CSP). However, non-stationarities in the data can negatively affect the performance of CSP, i.e. variation of the signal properties within and across experimental sessions coming from electrode artefacts, alpha or muscular activity, or fatigue may result in suboptimal projection directions. We alleviate this problem by regularizing CSP towards stationary subspaces and show that this especially increases classification accuracy of people who are not able to control a BCI i.e. have more than 30% of error. These users very often show non-stationarities in their EEG signals.


  Přepis řeči

|

  Slajdy

Zvětšit slajd | Zobrazit všechny slajdy

0:00:16

  1. slajd

0:00:32

  2. slajd

0:02:00

  3. slajd

0:03:29

  4. slajd

0:03:37

  5. slajd

0:06:23

  6. slajd

0:07:21

     6. slajd

0:09:15

  7. slajd

0:10:00

  8. slajd

0:10:14

  9. slajd

0:10:46

 10. slajd

0:11:01

 11. slajd

0:12:45

 12. slajd

0:15:52

     7. slajd

0:16:18

 13. slajd

0:16:31

     7. slajd

  Komentáře

Please sign in to post your comment!

  Informace o přednášce

Nahráno: 2011-05-27 09:50 - 10:10, Club H
Přidáno: 21. 6. 2011 17:34
Počet zhlédnutí: 75
Rozlišení videa: 1024x576 px, 512x288 px
Délka videa: 0:19:16
Audio stopa: MP3 [6.51 MB], 0:19:16