Simulation study on artifact elimination in EEG signals by artificial neural network

Review and analysis of continuous EEG recordings may be impeded by physiological artifacts such as blinks, eye movements, or cardiac activity. Many methods have been proposed to remove artifacts from EEG recordings, especially arising from eye movements and blinks. Often regression in the time or frequency domain is performed on EEG recordings to derive parameters characterizing the appearance and spread of eye artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing eye artifacts inevitably involves subtracting relevant EEG signals from each record as well.