epibox 2.0.5

EpiBOX is a Raspberry Pi tool for easy signal acquisition.

EpiBOX, the Python package

A Research Tool to Stimulate Collaboration Within Biosignal Collection

EpiBOX was developed as a way to enable researchers to escalate their data collection process by leveraging the human resources available. By providing a versatile, discreet, user-friendly and open-source system, operated through a mobile application, we hope to provide a collaboration tool for the acquisition of biosignals.

Designed for use with a Raspberry Pi due to its unobtrusive design (but usable with any Linux device), it acts as an autonomous recording unit - allowing for sensor connectivity and data storage. EpiBOX mobile app provides the user interface and the near-real time visualization of the data.

Currently, EpiBOX supports BITalino-based equipments allowing for the recording, storage and visualization of up to 12 channels simmultaneously. Nevertheless, this package can be easily integrated with other sensors, as long as a Python API is provided!

Requirements

• This Python package is complementary the mobile app EpiBOX (available at EpiBOX);
• It also requires a Raspberry Pi set up as a wireless access point and MQTT broker in order to ensure communication between the mobile app and the recording unit (RPi itself or another Linux device).

Installation

Use the package manager pip to install epibox.

pip install epibox
or 
pip install --upgrade epibox

Usage

# this will initiate the process - which should be continued by the user interface (EpiBOX app)
python -m epibox

Features

• Step-by-step interactions to start the acquisition
• History of acquisition devices
• Default configurations for optimized interaction
• Real-time visualization of up-to 12 channels
• In-acquisition annotations

Additional Resources

Why BITalino:

• Versatility of sensors & flexibility of wearable form-factors
• Rapid & cheap prototyping
• Peer-validated against gold-standards

Why Raspberry Pi:

• Discreteness
• Affordability
• Ease of system replication - through shell script or RPi imager
• Computational and storage power

Get to know our project @ LinkedIn - PreEpiSeizures

License

MIT

Contact

For any additional information about the mobile app or our project please contact me: [e-mail]

======= History

0.1.0 (2021-07-08)

• First release on PyPI.