EEGrunt: A Collection Python EEG (+ECG) Analysis Utilities

[READ THE ANNOUNCEMENT POST »][1]

Working with EEG (electroencephalography) data is hard, and this little library aims to make it easier. EEGrunt consists of a collection of functions for reading EEG data from CSV files, converting and filtering it in various ways, and finally generating pretty and informative visualizations.

Update: We’ve added functions to plot heart rate and heart rate variability from recorded OpenBCI ECG (electrocardiography) data. You can test these out with the analyzeecgchannel.py and analyzeecgdata.py demo scripts. We’ve posted a new tutorial on our blog to get you started: [EEGrunt update: Analyze heart rate and HRV with Python][2]

Features

• EEGrunt is compatible with data from OpenBCI and Muse.

• EEGrunt has bandpass, notch, and highpass filters for cleaning up powerline interference, OpenBCI's DC offset, and zeroing in on the frequency band you want to analyze.

• EEGrunt makes it easy to generate signal plots, amplitude trend graphs, spectrograms, and FFT (fast-fouier transform) graphs, etc.

Getting Started

• Download or clone the repo: git clone https://github.com/curiositry/EEGrunt
• Run sudo bash installlinuxdependencies.sh (tell me if this doesn’t work)
• Take a look in analyze_data.py and edit at will, or create your own script using EEGrunt.py. Make sure to set the required variables — device, path, and filename.
• Run it: python analyze_data.py
• [Read the announcement post for the official tutorial!][1]
• [Optional] Interested in [analyzing ECG data with EEGrunt][2]? Take a look at the [new tutorial][2].

[1]: http://www.autodidacts.io/eegrunt-open-source-python-eeg-analysis-utilities/ [2]: http://www.autodidacts.io/analyze-ecg-heart-rate-and-hrv-with-python-and-eegrunt/