Decoding cognitive brain states

Author

Porbadnigk, Anne K. ; Treder, Matthias Sebastian ; Fazli, Siamac ; Tangermann, M. ; Vidaurre, C. ; Haufe, Stefan ; Curio, Gabriel ; Blankertz, Benjamin ; Muller, Klaus-Robert

Author_Institution

Machine Learning Group, Berlin Inst. of Technol. (TU Berlin), Berlin, Germany

fYear

2013

fDate

18-20 Feb. 2013

Firstpage

16

Lastpage

18

Abstract

The last years have seen a rise in interest in using BCI methodology for investigating non-medical questions beyond the purpose of communication and control. This abstract first provides a short introduction to BCI challenges from a machine learning perspective. The remaining sections present selected applications of BCI discussing in particular the use of EEG in combination with BCI methods for investigating how signal quality is processed on a sensory and cognitive level.

Keywords

brain-computer interfaces; cognition; electroencephalography; learning (artificial intelligence); medical signal processing; BCI methodology; EEG; brain-computer interface; cognitive brain state decoding; cognitive level; electroencephalography; machine learning perspective; nonmedical question; sensory level; signal quality; Abstracts; Brain-computer interfaces; Degradation; Electroencephalography; Monitoring; Noise; Real-time systems; Applied Cognitive Neuroscience; Brain Computer Interfaces; Machine Learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Brain-Computer Interface (BCI), 2013 International Winter Workshop on

Conference_Location

Gangwo

Print_ISBN

978-1-4673-5973-3

Type

conf

DOI

10.1109/IWW-BCI.2013.6506613

Filename

6506613