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

被引:87
作者
Bao, Forrest Sheng [1 ]
Liu, Xin [2 ]
Zhang, Christina [3 ]
机构
[1] Texas Tech Univ, Dept Elect Engn, Dept Comp Sci, Lubbock, TX 79409 USA
[2] Nanjing Univ Posts & Telecommunicat, ECHO Labs, Nanjing 210003, Jiangsu, Peoples R China
[3] McGill Univ, Dept Phytol, Montreal, PQ H3G 1Y6, Canada
关键词
ALZHEIMERS-DISEASE; EEG; QUANTIFICATION; ENTROPY;
D O I
10.1155/2011/406391
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:7
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共 22 条
  • [1] Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
    Andrzejak, RG
    Lehnertz, K
    Mormann, F
    Rieke, C
    David, P
    Elger, CE
    [J]. PHYSICAL REVIEW E, 2001, 64 (06): : 8 - 061907
  • [2] Balli T, 2009, I IEEE EMBS C NEUR E, P707
  • [3] Bao F. S., 2010, P 32 INT C IEEE ENG
  • [4] Bao FS, 2009, IEEE ENG MED BIO, P6603, DOI 10.1109/IEMBS.2009.5332550
  • [5] A New Approach to Automated Epileptic Diagnosis Using EEG and Probabilistic Neural Network
    Bao, Forrest Sheng
    Lie, Donald Yu-Chun
    Zhang, Yuanlin
    [J]. 20TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, VOL 2, PROCEEDINGS, 2008, : 482 - +
  • [6] Dauwels J, 2008, LECT NOTES COMPUT SC, V4984, P112
  • [7] Localization of Seizure Onset Area from Intracranial Non-Seizure EEG by Exploiting Locally Enhanced Synchrony
    Dauwels, Justin
    Eskandar, Emad
    Cash, Sydney
    [J]. 2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 2180 - +
  • [8] Gardner AB, 2006, J MACH LEARN RES, V7, P1025
  • [9] APPROACH TO AN IRREGULAR TIME-SERIES ON THE BASIS OF THE FRACTAL THEORY
    HIGUCHI, T
    [J]. PHYSICA D-NONLINEAR PHENOMENA, 1988, 31 (02) : 277 - 283
  • [10] EEG ANALYSIS BASED ON TIME DOMAIN PROPERTIES
    HJORTH, B
    [J]. ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1970, 29 (03): : 306 - &