Metadata-Version: 2.1
Name: nmb-eeg
Version: 0.9
Summary: Power spectra of pure EEG from two temporarily paralysed subjects from Whitham et al 2007
Home-page: https://github.com/berndporr/nmb_eeg
Author: Bernd Porr
Author-email: bernd.porr@glasgow.ac.uk
License: GPL 3.0
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Dist: numpy

Pure EEG power during paralysis
===============================

Power spectra of pure EEG from two temporarily paralysed subjects.

Data from (Fig 1, B-traces):

`Scalp electrical recording during paralysis: Quantitative evidence that
EEG frequencies above 20 Hz are contaminated by EMG
Emma M. Whitham a , Kenneth J. Pope b , Sean P. Fitzgibbon c , Trent Lewis b ,
C. Richard Clark c , Stephen Loveless d , Marita Broberg e , Angus Wallace e ,
Dylan DeLosAngeles e , Peter Lillie f , Andrew Hardy f , Rik.
Clinical Neurophysiology Volume 118, Issue 8, August 2007,
Pages 1877-1888. <https://www.sciencedirect.com/science/article/abs/pii/S1388245707001988>`_

Please cite as "Data from ..." as outlined above. This has been advised by Elsevier's Copyrights Coordinator.


Usage
-----

To obtain the average PSD over all experiments just use
the default constructor::

  p = NMB_EEG_From_WhithamEtAl()


If you want to extract the PSD of dataset one do::

  p = NMB_EEG_From_WhithamEtAl(1)


Obtain the power spectral density in V^2/Hz use::

  psd = p.EEGVariance(f)

where `f` can be either a single frequency or a numpy array.
The lowest permitted frequency is
`f_signal_min` and the highest `f_signal_max`.

The total power of the entire frequency range from `f_signal_min` to `f_signal_max` is::

  totalEEGPower = p.totalEEGPower()


Because `EEGVariance(f)` accepts a numpy array plotting the spectrum is simply::

  f = np.linspace(p.f_signal_min,p.f_signal_max,100)
  plt.plot(f,p.EEGVariance(f))



Usage example
-------------

Run::

  plot_paralysed_EEG_PSD.py

which generates the plot at the top of this page.



Credit
------

Bernd Porr <bernd.porr@glasgow.ac.uk>


