The long-term objective of this proposal is to develop technology for removing artifacts from brain activity (EEG) measurements in order to allow automated EEG analysis. This capability will be important for clinical and nonclinical endeavors.The specific aim of this project is to develop a technique that can be implemented online in realtime for removing the EOG influence from the observed EEG. Given that all eye movements and blinks result in EOG electrical signals characterized by amplitude, frequency, and phase, an external drive signal applied near the eye with the full bandwidth of signal characteristics can emulate the natural EOG. This, along with the observation of this drive's influence on distant EEG electrodes, will allow an estimation of the attenuation factors, or transfer function, of this drive signal. This transfer function, then, can be used to correct the EEG by subtracting the weighted natural EOG. The feasibility and validity of this technique will be shown both statistically and analytically.National Institute of Neurological and Communicative Disorders and Stroke (NINDS)
