Artefact filtering from human EEG

The computer EEG data processing is modern trend in medical data processing. The computer processing is needful especially for long-term EEG data. Long-term EEG records of patients with diagnosis of epilepsy are registered during normal every day regime, where EEG record is contaminated not only by outside influence, but even by physiological activity of patient (e.g. breathing, moving of limbs, etc.). These activities from the point of clinical neurological interest are contamination and they have to be removed. This paper is dedicated to solving of removing artefacts of physiological origin in EEG data and gives complex solution of this problem from the adaptive segmentation of EEG signal over identification of each segment of signal to adaptive filtering