An EEG artifact identification embedded system using ICA and multi-instance learning
ISCAS, pp. 1-4, 2017.
Electroencephalogram (EEG) data is used for a variety of purposes, including brain-computer interfaces, disease diagnosis, and determining cognitive states. Yet EEG signals are susceptible to noise from many sources, such as muscle and eye movements, and motion of electrodes and cables. Traditional approaches to this problem involve super...More
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