DECODING OF UPPER LIMB MOVEMENT BY FRACTAL ANALYSIS OF ELECTROENCEPHALOGRAM (EEG) SIGNAL

Abstract

Analysis of human movements is an important category of research in biomedical engineering, especially for the rehabilitation purpose. The movement of limbs is investigated usually by analyzing the movement signals. Less efforts have been made to investigate how neural that correlate to the movements, are represented in the human brain. In this research, for the first time we decode the limb movements by fractal analysis of Electroencephalogram (EEG) signals. We investigated how the complexity of EEG signal changes in different limb movements in motor execution (ME), and motor imagination (MI) sessions. The result of our analysis showed that the EEG signal experiences greatest level of complexity in elbow flexion and hand-close movements in ME, and MI sessions respectively. On the other hand, the lowest level of complexity of EEG signal belongs to hand-open and rest condition in ME, and MI sessions, respectively. Employing fractal theory in analysis of bio signals is not limited to EEG signal, and can be further investigated in other types of human’s bio signals in different conditions. The result of these investigations can vastly been employed for the rehabilitation purpose.