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Python in Brain-Computer Interfaces (BCI): Development of a BCI based on Motor imagery

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2 Author(s)
Luz Maria Alonso-Valerdi ; School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom ; Francisco Sepulveda

Brain-Computer Interfaces (BCI) give rise to a communication means between individuals with severe motor disorders, and their external world via the measurement of the electroencephalographic (EEG) activity. BCI users may control this activity by concentrating on a specific mental task. Motor imagery (MI) executions have become the most used mental task by BCI-groups. Despite a large number of references describing the theoretical framework of MI-based BCIs, there is not enough information related to the available computer software that could be suitable to develop a specific-purpose, efficient and straightforward BCI. Therefore, the aims of this paper are: (1) to develop a MI-based BCI system making use of Python programming language, and (2) to study MI signals of three users via the proposed BCI system in order to adapt a computer for posterior applications. The use of Python along with plug-ins for developing MI-based BCI systems is not only feasible, but also it is proficient. Moreover, the Python community provides extensive variety of tools to design compelling systems.

Published in:

Computer Science and Electronic Engineering Conference (CEEC), 2011 3rd

Date of Conference:

13-14 July 2011