project to receive data from Muse headband
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Collects EEG data from FP1, TP9, TP10, FP2 (10-20 System)
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Uses FFT to extract the power in the theta, alpha, beta and gamma frequency bands
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Training data collected for a 'relax' phase and a 'focus' phase
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Currently using k-nn algorithm to classify new testing data into one of the 2 classes (relax, focus) using standardized Euclidean distance
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Implemented a 10-fold cross validation to determine the accuracy of the k-nn algorithm using different k values
- Able to achieve ~90% accuracy with k values 5-15
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End Goal: Use the developed classification technique to control the mobile device
- E.g. Playing a game using 'mind control'
- E.g. Identifying periods of relaxation and concentration while user is performing some task on the mobile device
#-------------------- local folder -> D:/workspace/GitHub/MuseIO-EEGreceiver