Tutorial on multimodal neuroimaging for brain-computer interfacing

Author

Fazli, Siamac ; Muller, Klaus-Robert ; Lee, Sang-Rim ; Blankertz, Benjamin

Author_Institution

Neurotechnology & Machine Learning Groups, Berlin Inst. of Technol. (TU Berlin), Berlin, Germany

fYear

2013

fDate

18-20 Feb. 2013

Firstpage

1

Lastpage

2

Abstract

Multimodal techniques have seen a rising interest from the neuroscientific as well as the BCI community in recent times. In this abstract two aspects of multi-modal imaging will be reviewed. Firstly, how recordings of multiple subjects can help in finding subject-independent BCI classifiers and secondly how multi-modal neuroimaging methods, namely combined EEG and NIRS measurements can help in enhancing as well as robustifying BCI performance.

Keywords

brain-computer interfaces; electroencephalography; image classification; infrared spectra; medical image processing; neurophysiology; BCI community; EEG measurement; NIRS measurement; brain-computer interface; electroencephalography; multimodal neuroimaging; multimodal technique; near infrared spectroscopy; subject-independent BCI classifier; Brain modeling; Brain-computer interfaces; Calibration; Electrodes; Electroencephalography; Neuroimaging; Robustness; Brain Computer Interfacing, Subject; Multimodal Neuroimaging; independent classifiers;

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.2013.6506605

Filename

6506605