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An ANN Approach to EEG Scoring

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									An ANN Approach to EEG
Scoring
Anand Lakshmanan
ECE 539
Dec 12 , 2001
Introduction
•   EEG – Electroencephalogram
•   Measures brain activity.
•   Used to diagnose and cure brain
    related disorders. EEG is often
    contaminated with eye
    artefacts..eg blinks.
•   These “extra” signals are currently
    removed manually during data
    analysis.
•   Involves time and money.
•   I have used ANN modeled on
    Startle blink under noise.
Data Collection & Preprocessing

•   Source : Personal Involvement in experiment set up for data collection at The
    Psychology Department UW Madison.
•   43 subjects * 21sessions * 10000 = data points for classification.
•   DOS Snapshot Stream – Software by the company HEM Data Corp. This
    program collects data from channels as per the specified sampling rate and
    gain settings of an attached Bio-Electric Amplifier.
•   Hardware Contour following Integration of Raw Startle Data.
•   The data is streamed to a stimulus file.
•   Matlab used to read the stimulus file.
•   Scaling of data.
•   60 Hz digital software notch filtering using Matlab Signal Processing ToolBox
Approach

• Pattern Classification problem that
  distinguishes EEG from Eye Artefact
• MLP with back propagation.
• Program written on the lines of the all
  powerful “bp.m” written by Prof .Hu
Results and Future

• I tried out several combinations and trained the
  network extensively.
• Attractive classification rate of 90% so far using
  learn rate = 0.01 and momentum = 0.4 on a 3
  layer MLP with 2 neurons in hidden layer.
• Yet to do cross validation and hopefully Crate
  will improve.

								
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