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Task: Brain-computer interface
Metapackage: false
Install: true
Description: Debian Science Brain-computer interface packages
Debian Science packages for the design and use of
brain-computer interface (BCI) -- direct communication pathway
between a brain and an external device. BCIs are often aimed
at assisting, augmenting or repairing human cognitive or
sensory-motor functions.
.
The selection of packages is targeting the complete frameworks for
the design of BCI systems. Often such systems rely on external
presentation, data collection and analysis software which could be
found in science-neuroscience-cognitive, science-dataacquisition,
data-machine-learning metapackages.
; Added by blends-inject 0.0.6. [Please note here if modified manually]
Suggests: pyff
Homepage: http://bbci.de/pyff/
Language: Python
License: GPL-2+
Vcs-Browser: https://github.com/venthur/pyff
Vcs-Git: git://github.com/venthur/pyff.git
Pkg-Description: Brain Computer Interface (BCI) framework
Pyff is a Pythonic Feedback Framework which provides a platform
independent framework to develop BCI feedback applications in
Python. It was designed to make the development of feedback
applications as easy as possible. Pyff framework moves feedback
implementations to a general purpose, and easy to learn language like
Python. Python provides many so called bindings to other libraries,
which allow it to develop high quality multimedia feedback
applications, with little effort.
.
The framework communicates with the rest of the BCI system via a
standardized communication protocol using UDP and XML and is
therefore suitable to be used with any BCI system that may be adapted
to send its control signal via UDP in the specified format.
Published-Authors: Bastian Venthur, Simon Scholler, John Williamson, Sven Dähne, Matthias S Treder, Maria T Kramarek, Klaus-Robert Müller and Benjamin Blankertz
Published-DOI: 10.3389/fnins.2010.00179
Published-In: Frontiers in Neuroscience
Published-Title: Pyff --- A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience
Published-Year: 2010
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Suggests: pybci
Homepage: http://pybci.sourceforge.net/
Language: Python, C++
License: MIT
Vcs-Browser: http://pybci.git.sourceforge.net/git/gitweb-index.cgi
Vcs-Git: git://pybci.git.sourceforge.net/gitroot/pybci/pybci
Pkg-Description: Brain Computer Interface module for Brain Vision Recorder
This module gives you the possibility to create a Brain Computer
Interface (BCI), and herewith to get EEG data online and evaluate the
data while you are receiving it. The module is made for all users of
the Brain Vision Recorder because of the therein implemented function
of Remote Data Access. It is not possible to use it with another EEG
Recorder Software, but this will be a project in the future.
.
Using the PyBCI module, you are able to get a numpy data array in up
to every few ten milliseconds and therewith evaluate the data almost
in realtime with other powerful Python packages, for example using
PyMVPA.
Remark: No activity since Sep 2009
; Added by blends-inject 0.0.6. [Please note here if modified manually]
Suggests: bcpy2000
Homepage: http://bci2000.org/downloads/BCPy2000/BCPy2000.html
Language: Python, C++
License: LGPL-3+ and GPL-3+ and non-free (BCI2000)
Pkg-Description: platform for brain-computer interface systems
BCPy2000 provides a platform for rapid, flexible development of
experimental brain-computer interface systems. It is based on, and
hosted by, the BCI2000 project. From the developer's point of view,
the implementation is carried out in Python, taking advantage of
various high-level packages: VisionEgg for stimulus presentation,
NumPy and SciPy for signal processing and classification, and IPython
for interactive debugging.
.
Being a BCI2000 system, it is modular, consisting of an Application
module (the stimulus presentation part), a Signal Processing module
(the machine-learning part), and a Signal Source module (the toy data
generation part). You can choose to use Python to implement one, two,
or all three of these modules, and use other pre-existing BCI2000
modules for the remainder of the system (for example, for the Signal
Source, you can choose from BCI2000's comprehensive range of EEG
acquisition modules). The modules communicate over TCP/IP, so they
can run on different machines (and possibly different operating
systems) if necessary.
; Added by blends-inject 0.0.6. [Please note here if modified manually]
Suggests: bci2000
Homepage: http://bci2000.org
Language: C++
License: non-free (non-redistributable, non-commercial)
Pkg-Description: platform for brain-computer interface systems
BCI2000 supports a variety of data acquisition systems, brain
signals, and study/feedback paradigms. During operation, BCI2000
stores data in a common format (BCI2000 native or GDF), along with
all relevant event markers and information about system
configuration. BCI2000 also includes several tools for data
import/conversion (e.g., a routine to load BCI2000 data files
directly into Matlab) and export facilities into ASCII.
.
BCI2000 also facilitates interactions with other software. For
example, Matlab scripts can be executed in real-time from within
BCI2000, or BCI2000 filters can be compiled to execute as stand-alone
programs. Furthermore, a simple network-based interface allows for
interactions with external programs written in any programming
language. For example, a robotic arm application that is external to
BCI2000 may be controlled in real time based on brain signals
processed by BCI2000, or BCI2000 may use and store along with brain
signals behavioral-based inputs such as eye-tracker coordinates.
Registration: http://www.bci2000.org/MTA
Remark: Besides non-commercial restriction, it is required that
"ACADEMIC USER must be an investigator / lab director (and not a
post-doc or student)". Re-distribution (to third-party) is also
forbidden.
; Added by blends-inject 0.0.6. [Please note here if modified manually]
Suggests: emokit
Homepage: https://github.com/daeken/Emokit
Language: Python, C
License: BSD-3
Vcs-Browser: https://github.com/daeken/Emokit
Vcs-Git: git://github.com/daeken/Emokit.git
Pkg-Description: Emotiv EPOC headset Python interface
Emotive is an interface to a budget Emotiv EPOC EEG headset.
; Added by blends-inject 0.0.6. [Please note here if modified manually]
Suggests: openvibe
Homepage: http://openvibe.inria.fr
Language: C++
WNPP: 580247
License: LGPL
Pkg-Description: platform for the design, test and use of BCI
OpenViBE enables to design, test and use Brain-Computer Interfaces (BCI).
OpenViBE is a software for real-time neurosciences (that is, for
real-time processing of brain signals). It can be used to acquire, filter,
process, classify and visualize brain signals in real time.
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