Debian Science Brain-computer interface packages

Emotive is an interface to a budget Emotiv EPOC EEG headset.

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.

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.

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.

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.

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.