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A real-time tool for acquisition, analysis and stimuli delivery for OpenBCI.

Project description

Developed by Yeison Nolberto Cardona Álvarez
Andrés Marino Álvarez Meza, PhD.
César Germán Castellanos Dominguez, PhD.
Digital Signal Processing and Control Group | Grupo de Control y Procesamiento Digital de Señales (GCPDS)
Universidad Nacional de Colombia sede Manizales


BCI-Framework

A distributed processing tool, stimuli delivery, psychophysiological experiments designer and real-time data visualizations for OpenBCI.

GitHub top language PyPI - License PyPI PyPI - Status PyPI - Python Version GitHub last commit CodeFactor Grade Documentation Status

BCI-Framework is an open-source tool for the acquisition of EEG/EMG/ECG signals, developed to work with OpenBCI's Cyton board, the main core of this software lies on OpenBCI-Stream, a library designed to handle all the low-level hardware features and extend the hardware capabilities with high-level programming libraries.

An optionally distributed paradigm for data acquisition and streaming is available to be implemented, this approach stabilizes the sampling rate on non-real-time acquisition systems and consists on delegate the board handle to a dedicated environ and stream out the data in real-time. Write custom visualization for raw or processed time series and design custom neurophysiological experiments are the major features available in this application.

BCI-Framework comprises a graphical user interface (GUI) with a set of individual computational processes (distributed or in a single machine), that feed a visualization, serve a stimuli delivery, handle an acquisition, storage data, or stream a previous one (offline analysis). It has a built-in development environment and a set of libraries that the user can implement to create their specific functionality.

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1.2.4

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