Wyrm, A Pythonic Toolbox for Brain-Computer Interfacing
Bastian Venthur, Benjamin Blankertz
TL;DR
Wyrm is a versatile Python toolbox designed for brain-computer interfacing, supporting real-time and offline data analysis, suitable for various neuroscientific applications.
Contribution
This paper introduces Wyrm, a new Python-based toolbox that simplifies BCI signal processing for both online experiments and offline analysis.
Findings
Supports real-time BCI experiments
Enables offline data visualization
Applicable to diverse neuroscientific problems
Abstract
A Brain-Computer Interface (BCI) is a system that measures central nervous system activity and translates the recorded data into an output suitable for a computer to use as an input signal. Such a BCI system consists of three parts, the signal acquisition, the signal processing and the feedback/stimulus presentation. In this paper we present Wyrm, a signal processing toolbox for BCI in Python. Wyrm is applicable to a broad range of neuroscientific problems and capable for running online experiments in real time and off-line data analysis and visualisation.
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · Neural dynamics and brain function · Advanced Memory and Neural Computing