Wyrm, A Pythonic Toolbox for Brain-Computer Interfacing
This provides a practical solution for researchers and developers in neuroscience and BCI fields, though it is incremental as it builds on existing Python toolboxes.
The authors tackled the need for a versatile signal processing toolbox in brain-computer interfacing by developing Wyrm, a Python-based tool that supports both online real-time experiments and offline data analysis and visualization.
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.