| Name | bci-framework JSON |
| Version |
1.3.1
JSON |
| download |
| home_page | |
| Summary | A real-time tool for acquisition, analysis and stimuli delivery for OpenBCI. |
| upload_time | 2023-06-21 19:28:41 |
| maintainer | Yeison Cardona |
| docs_url | None |
| author | Yeison Cardona |
| requires_python | >=3.8 |
| license | BSD-2-Clause |
| keywords |
|
| VCS |
 |
| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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> Developed by [Yeison Nolberto Cardona Álvarez](https://github.com/yeisonCardona)
[Andrés Marino Álvarez Meza, PhD.](https://github.com/amalvarezme)
César Germán Castellanos Dominguez, PhD.
> _Digital Signal Processing and Control Group_ | _Grupo de Control y Procesamiento Digital de Señales ([GCPDS](https://github.com/UN-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.
[](https://bci-framework.readthedocs.io/en/latest/?badge=latest)
BCI-Framework is an open-source tool for the acquisition of EEG/EMG/ECG signals, developed to work with [OpenBCI's Cyton board](https://shop.openbci.com/products/cyton-biosensing-board-8-channel?variant=38958638542), the main core of this software lies on [OpenBCI-Stream](https://openbci-stream.readthedocs.io/en/latest/index.html), a library designed to handle all the [low-level hardware features](https://docs.openbci.com/docs/02Cyton/CytonSDK) 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](70-develop_visualizations.ipynb) for raw or processed time series and [design custom neurophysiological experiments](80-stimuli_delivery.ipynb) 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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