Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-9871
For citation please use:
Main Title: Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment
Author(s): Brandl, Stephanie
Höhne, Johannes
Müller, Klaus-Robert
Samek, Wojciech
Type: Conference Object
Is Supplemented By: 10.14279/depositonce-9827
Language Code: en
Abstract: Bringing Brain-Computer Interfaces (BCIs) into everyday life is a challenge because an out-of-lab environment implies the presence of variables that are largely beyond control of the user and the software application. This can severely corrupt signal quality as well as reliability of BCI control. Current BCI technology may fail in this application scenario because of the large amounts of noise, nonstationarity and movement artifacts. In this paper, we systematically investigate the performance of motor imagery BCI in a pseudo realistic environment. In our study 16 participants were asked to perform motor imagery tasks while dealing with different types of distractions such as vibratory stimulations or listening tasks. Our experiments demonstrate that standard BCI procedures are not robust to theses additional sources of noise, implicating that methods which work well in a lab environment, may perform poorly in realistic application scenarios. We discuss several promising research directions to tackle this important problem.
URI: https://depositonce.tu-berlin.de/handle/11303/10980
http://dx.doi.org/10.14279/depositonce-9871
Issue Date: 2-Jul-2015
Date Available: 8-Apr-2020
DDC Class: 006 Spezielle Computerverfahren
Subject(s): brain-computer interface
BCI
out-of-lab environment
motor imagery
distraction
performance evaluation
Sponsor/Funder: BMBF, 01GQ1115, Adaptive Gehirn-Computer-Schnittstellen (BCI) in nichtstationären Umgebungen
License: http://rightsstatements.org/vocab/InC/1.0/
Proceedings Title: 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Publisher Place: New York, NY [u.a.]
Publisher DOI: 10.1109/NER.2015.7146600
EISSN: 1948-3554
ISBN: 978-1-4673-6389-1
ISSN: 1948-3546
Appears in Collections:FG Maschinelles Lernen » Publications

Files in This Item:
brandl_etal_2015.pdf

Accepted manuscript

Format: Adobe PDF | Size: 651.57 kB
DownloadShow Preview
Thumbnail

Item Export Bar

Items in DepositOnce are protected by copyright, with all rights reserved, unless otherwise indicated.