Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.629094
Title: Detecting freezing of gait in Parkinson's disease for automatic application of rhythmic auditory stimuli
Author: Khan, Ali Asad
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 2013
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Abstract:
Freezing of Gait (FOG) is a neuro-motor symptom associated with Parkinson's disease (PD), which is suitably managed by Rhythmic Auditory Stimulation (RAS) and music therapy, if applied upon or prior to symptom onset. This stipulates an objective measurement of gait to automatically detect FOG. This research has improved on existing methods for automatic detection of freeze states using vertical acceleration of the leg. Accordingly, a method was devised, implemented and evaluated with the DAPHNet Freezing of Gait dataset. The proposed method is based on Discrete Wavelet Transform (DWT) for feature extraction and Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel to distinguish freezing of gait from normal locomotion in a binary classification problem. The method was evaluated on the DAPHNet dataset containing over 8 hours of recorded data from PD patients with a history of FOG. The performance of the method was examined in user-dependent and user-independent experimental scenarios with respect to the analysis of feature combinations and sliding window size. The evaluated method exceeded the state-of-the-art performance results in user-independent settings giving an average sensitivity of 76.37% and an average specificity of 85.15% with a maximum detection latency of 2 seconds.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.629094  DOI: Not available
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