• Wyrm: A Brain-Computer Interfa...

Treffer: Wyrm: A Brain-Computer Interface Toolbox in Python.

Title:
Wyrm: A Brain-Computer Interface Toolbox in Python.
Authors:
Venthur B; Department of Neurotechnology, Technische Universität Berlin, Sekr. MAR 4-3 Marchstraße 23, 10587, Berlin, Germany. bastian.venthur@tu-berlin.de., Dähne S; Department of Neurotechnology, Technische Universität Berlin, Sekr. MAR 4-3 Marchstraße 23, 10587, Berlin, Germany.; Department of Machine Learning, Technische Universität, Berlin, Germany.; Bernstein Center for Computational Neuroscience, Berlin, Germany., Höhne J; Department of Neurotechnology, Technische Universität Berlin, Sekr. MAR 4-3 Marchstraße 23, 10587, Berlin, Germany., Heller H; Department of Neurotechnology, Technische Universität Berlin, Sekr. MAR 4-3 Marchstraße 23, 10587, Berlin, Germany., Blankertz B; Department of Neurotechnology, Technische Universität Berlin, Sekr. MAR 4-3 Marchstraße 23, 10587, Berlin, Germany.
Source:
Neuroinformatics [Neuroinformatics] 2015 Oct; Vol. 13 (4), pp. 471-86.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Humana Press, Inc Country of Publication: United States NLM ID: 101142069 Publication Model: Print Cited Medium: Internet ISSN: 1559-0089 (Electronic) Linking ISSN: 15392791 NLM ISO Abbreviation: Neuroinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: Totowa, NJ : Humana Press, Inc., c2003-
MeSH Terms:
Brain Mapping* , Brain-Computer Interfaces* , Programming Languages* , Software*, Brain/*physiology, Algorithms ; Animals ; Electroencephalography ; Evoked Potentials/physiology ; Humans ; Imagery, Psychotherapy ; Machine Learning
References:
J Neural Eng. 2013 Oct;10(5):056014. (PMID: 23985960)
IEEE Trans Rehabil Eng. 2000 Dec;8(4):441-6. (PMID: 11204034)
Front Neuroinform. 2013 Dec 24;7:40. (PMID: 24399965)
Behav Brain Funct. 2010;6:28. (PMID: 20509913)
Neuroimage. 2011 May 15;56(2):814-25. (PMID: 20600976)
Conf Proc IEEE Eng Med Biol Soc. 2012;2012:1786-8. (PMID: 23366257)
Comput Intell Neurosci. 2011;2011:156869. (PMID: 21253357)
IEEE Trans Rehabil Eng. 2000 Jun;8(2):174-9. (PMID: 10896179)
Front Neurosci. 2013 Dec 26;7:267. (PMID: 24431986)
J Neural Eng. 2010 Oct;7(5):056013. (PMID: 20858924)
Front Neurosci. 2010 Dec 02;4:179. (PMID: 21160550)
Neuroimage. 2014 Feb 1;86:111-22. (PMID: 23954727)
IEEE Trans Biomed Eng. 2004 Jun;51(6):1034-43. (PMID: 15188875)
Neuroimage. 2014 Feb 15;87:96-110. (PMID: 24239590)
IEEE Trans Neural Syst Rehabil Eng. 2006 Jun;14(2):153-9. (PMID: 16792282)
Contributed Indexing:
Keywords: BCI; Brain-computer interface; ECoG; EEG; Machine learning; Python; Signal processing; Toolbox
Entry Date(s):
Date Created: 20150524 Date Completed: 20160808 Latest Revision: 20191210
Update Code:
20250114
PubMed Central ID:
PMC4626531
DOI:
10.1007/s12021-015-9271-8
PMID:
26001643
Database:
MEDLINE

Weitere Informationen

In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foundation for scientific computing in Python and machine learning packages like scikit-learn or packages for data analysis like Pandas are building on top of it. In this paper we present Wyrm ( https://github.com/bbci/wyrm ), an open source BCI toolbox in Python. Wyrm is applicable to a broad range of neuroscientific problems. It can be used as a toolbox for analysis and visualization of neurophysiological data and in real-time settings, like an online BCI application. In order to prevent software defects, Wyrm makes extensive use of unit testing. We will explain the key aspects of Wyrm's software architecture and design decisions for its data structure, and demonstrate and validate the use of our toolbox by presenting our approach to the classification tasks of two different data sets from the BCI Competition III. Furthermore, we will give a brief analysis of the data sets using our toolbox, and demonstrate how we implemented an online experiment using Wyrm. With Wyrm we add the final piece to our ongoing effort to provide a complete, free and open source BCI system in Python.