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EEGanalysisPython

PythonImplementation

q1.py: Using EEG data, developing a prediction model for eyes open and closed task. Data is raw at 256Hz,4 channels epoched and labelled. Various steps were used:

  1. Data was cleaned, filtered and then ICA was done.
  2. Alpha power was extracted.
  3. KNN classifier was used with 10 fold cross validation to develop a classification model.

q2.py: 1)Time -frequency decompostion of eeg data. 2) Temporal analysis of the dominant freq and see how it evolves over the tasks.

q3.py:

  1. Charactorizing signal components into various artifacts like eye blinks, muscle activity, eye movement, eyes open/closed.
  2. Performing ICA and then analyzing its time-frequency activity to look for the standard signatures of the above artifacts.