Brain computer interface based on electroencephalographic data (EEG data) with the help of machine learning algorithms.
Using a subject’s EEG reading, infer what he or she is thinking about or doing - (motion) A or B in a t0 to tn timeframe.
• Process EEG datas (parsing and filtering)
• Implement a dimensionality reduction algorithm
• Use the pipeline object from scikit-learn
• Classify a data stream in "real time"
Dataset can be downloaded here : https://physionet.org/content/eegmmidb/1.0.0/