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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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