Average Partial Power Spectrum Density For Motor Imagery Classification Using EEG

In this paper, we proposed an average partial power spectrum density method to classify mental tasks. The relevant mental tasks are: left hand movement, right hand movement and rest. The proposed method is the combination of a 2 Hz bandpass filter and an Average Partial Power Spectrum Density (APPSD) algorithm in the specific frequency ranges to find out features of imagery. From the obtained features of movements, an Artificial Neuron Network (ANN) model was used to classify imagery status. Experiments were performed on 2 subjects with 200 runs per subject to illustrate the effectiveness of the proposed method.
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