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Mining an EEG dataset for CSC493

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Final project for data mining CSC493.

Novi Sandlin
Luke Moore
Ramon ...
Garrett Lee


Dataset Description:

Using a cap with 32 integrated electrodes, EEG data were collected from three subjects while they performed three activities:
imagining moving their left hand, imagining moving their right hand, and thinking of words beginning with the same letter.
As well as the raw EEG signals, the data set provides precomputed features obtained by spatially filtering these signals
and calculating the power spectral density. (https://www.inf.ed.ac.uk/teaching/courses/dme/html/datasets0405.html)

Dataset MetaData:

31216 records in training data, 10464 in test data
Each record has 96 continuous values and a numerical label
63 MB as uncompressed text

Task/Challenges:

Perform exploratory data analysis to get a good feel for the data and prepare the data for data mining.
Train classifiers to assign class labels to indicate which activity the subject was performing while the data were collected.

-> INPUT: 96 personal EEG biosignals from neurode cap

-> OUTPUT: motor function classification (i.e., moving arm right, moving arm left, speaking)

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Mining an EEG dataset for CSC493

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