Published in

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

DOI: 10.1109/embc.2015.7319910

Links

Tools

Export citation

Search in Google Scholar

An EEG Study of Turning Freeze in Parkinson's Disease Patients: The Alteration of Brain Dynamic on the Motor and Visual Cortex

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Freezing of gait is a very debilitating symptom affecting many patients with Parkinson's disease, leading to a reduced mobility and increased risk for falls. Turning is known to be the most provocative trigger for freezing of gait. However, the underlying brain dynamic changes associated with a turning freeze remain unknown. This study therefore used ambulatory EEG to investigate the brain dynamic changes associated with freezing of gait during turning. In addition, this study aimed to determine the most suitable EEG sensor location to detect freezing of gait during turning using our classification system. Data from four Parkinson's disease patients with freezing of gait was analysed using power spectral density and brain effective connectivity, comparing periods of successful turning with freezing of gait during turning. Results showed that freezing of gait during turning is associated with significant alterations in the high beta and theta power spectral densities across the occipital and parietal areas. Furthermore, brain effective connectivity showed that freezing during turning was associated with increased connectivity towards the visual area, which also had the highest accuracy to detect freezing episodes in the O1 regions by using power spectral density in our classification analyses. This is the first study to show cortical dynamic changes associated with freezing of gait during turning, providing valuable information to enhance the performance of future freezing of gait detection systems.