The Exploration of EEG Signal during the Freezing of Gait in Parkinson Disease using EEGLAB Toolbox

Abstract

Parkinson’s disease (PD) is the second most common age related neurodegenerative disorder, affecting approximately 1-2% of the elderly population. Freezing of Gait (FOG) is a very disabling feature of PD that causes frequent falls. During FOG, patients are suddenly unable to take a step despite the intention to walk or continue moving forward. The neural mechanisms of FOG are unclear and treatments have only limited effectiveness. To detect FOG, using parameters extracted from the Electroencephalogram (EEG) is one of the most promising methods. The paper introduces the method of using the EEGLAB toolbox to explore the EEG pattern during the FOG event. These algorithms have been developed and applied successfully to calculate Power Spectra, Centroid Frequency and then plot the pattern of the scalp maps in the freezing stage. The finding shows that EEGLAB toolbox is the powerful to detect the changes of EEG signal, which is the recommendation for further EEG researches.