Development of Soft Computing Algorithms for the Analysis and Prediction of Motor Task from EEG data

Abstract

The aim of this research has been to first, acquire a solid understanding of electroencephalogram (EEG) and then contribute scientifically to advance the frontiers of this field. A prerequisite to achieve my defined goals was to understand the fundamentals of the neurophysiological processes that occur within the brain as much as possible. Another area that needed to be researched was the evidence related to movement preparation and planning. Moreover, observing EEG data in practical issues and how it is used to help humans with disability challenges seemed equally important. The objectives of this research are listed below: • To understand the EEG and be able to interpret mental activities with special focus on the time interval associated with movement planning and movement preparation. • Review of the current researches on analysis of EEG recordings prior to a movement or imagination of a movement and their effect on brain computer interfacing. • Design of novel algorithms for extraction and detection of the electric potentials happening before any voluntary movement. • Understanding of on-line analysis of EEG data and, hence, brain computer interfacing in communication, e.i. P300-Speller paradigm.