EEG epilepsy diagnosis

R package developed to extract features from multivariate time series from EEG data and feed them into a random forest classifier.

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Cite this software

What EEG epilepsy diagnosis can do for you

As this was a short lasting project, we mainly focused on processing multi-variate EEG (Electroencephalography) data as a proof of concept.

The software handles the data format and structure used in one particular study carried out by colleagues from Utrecht University in data collected in sub-saharan Africa, but uses generic external libraries (caret) for the machine learning.

This software was developed as part of the Young eScience Award 2015 (awarded to Wim Otte in 2015, but project took place in 2016).
The project description can be found here https://www.esciencecenter.nl/project/diagnosis-of-active-epilepsy-in-resource-poor-setting
A technical report on the project can be found here:https://www.biorxiv.org/content/10.1101/324954v1

Keywords
Programming languages
  • R 98%
  • Rebol 2%
License
</>Source code

Participating organisations

Netherlands eScience Center
Utrecht University

Contributors

Vincent van Hees
Vincent van Hees

Related projects

Diagnosis of active epilepsy in resource-poor setting

Prediction models based on EEG characteristics

Updated 15 months ago
Finished