Automatic identification of artifacts and unwanted physiologic signals in EEG and EOG during wakefulness

A set of computationally inexpensive methods for reliable and robust detection of undesired signals in the EEG and EOG was designed, implemented, and tested. This strategy includes detection of eye blinking, eye movements, muscle activity, and flat lines in multichannel EEG and EOG data. The proposed methodology was verified on real awake data acquired in controlled conditions (44 recordings of total length 26.38 h) during Maintenance of...