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Computational Intelligence and Neuroscience
Volume 2011 (2011), Article ID 406391, 7 pages
Research Article

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

1Department of Computer Science, Department of Electrical Engineering, Texas Tech University, Lubbock TX 79409-3104, USA
2ECHO Labs, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
3Department of Physiology, McGill University, Montreal, QC, Canada H3G 1Y6

Received 31 August 2010; Revised 26 October 2010; Accepted 31 December 2010

Academic Editor: Sylvain Baillet

Copyright © 2011 Forrest Sheng Bao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.