The detection of Freezing of Gait in Parkinson's disease patients using EEG signals based on Wavelet decomposition.

A. M. Ardi Handojoseno, James M. Shine, Tuan N. Nguyen, Yvonne Tran, Simon J. G. Lewis, Hung T. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

51 Citations (Scopus)

Abstract

Freezing of Gait (FOG) is one of the most disabling gait disturbances of Parkinson's disease (PD). The experience has often been described as "feeling like their feet have been glued to the floor while trying to walk" and as such it is a common cause of falling in PD patients. In this paper, EEG subbands Wavelet Energy and Total Wavelet Entropy were extracted using the multiresolution decomposition of EEG signal based on the Discrete Wavelet Transform and were used to analyze the dynamics in the EEG during freezing. The Back Propagation Neural Network classifier has the ability to identify the onset of freezing of PD patients during walking using these features with average values of accuracy, sensitivity and specificity are around 75 %. This results have proved the feasibility of utilized EEG in future treatment of FOG.

Original languageEnglish
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages69-72
Number of pages4
ISBN (Electronic)9781457717871
ISBN (Print)9781424441198
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: 28 Aug 20121 Sep 2012

Conference

Conference34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period28/08/121/09/12

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