Abstract
Gait Initiation Failure (GIF) is one of the most disabling gait disturbances seen in advanced Parkinson's disease (PD). Gait Initiation is a complex motor task that requires motor and cognitive processing to enable the correct selection, timing and scaling of movement. Failure to initiate the first step often precipitates falls and leads to significant morbidity. However, the brain mechanisms underlying GIF remain unknown. This study utilized an ambulatory electroencephalography (EEG) technique to investigate the brain dynamic changes underlying GIF and aims to detect the occurrence of GIF in four PD patients. We sought to determine whether episodes of GIF might be associated with a characteristic brain signal that could be detected by surface EEG. This preliminary investigation analyzed the EEG signals through power spectra density (PSD) and centroid frequency (CF) to show that the GIF episodes were associated with significant increases in the high beta band (21-38Hz) across the central, frontal, occipital and parietal EEG sites. By implementing PSD and CF as input features with two-layer Back Propagation neural networks as a classifier, the proposed system was able to detect GIF events with a classification performance of 84.27% sensitivity and 84.80% accuracy. This is the first study to show cortical dynamic changes associated with GIF in Parkinson's disease, providing valuable information to enhance the performance of future GIF detection that could be translated into clinical practice.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.