Detection and classification of brainwaves using digital signal processing techniques
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[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI SYSTEM AT AUTHOR'S REQUEST.] Different activities of our human brain can be detected as different brainwaves. The brainwaves are divided into different types based on their frequencies. This thesis is focused on the study of four types of brainwaves -Theta waves (4-8Hz), Alpha waves (8-12Hz), Beta waves (12-30Hz) and Gamma waves (30-80Hz). Each brainwave consists of bursts, therefore, we study the brainwaves through the bursts. The research contains two main parts, the first one is the detection of the bursts in different brainwaves, several methods -- bandpass filter, linear prediction, etc. -- are applied to reach better detection results. The second part is to classify the brainwaves that we have detected. We use three methods for the classification: 4-branch bandpass filter method, fast Fourier transform method and modified covariance method.
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