Prediction of freezing of gait in patients with Parkinson’s disease using EEG signals

A. M.Ardi Handojoseno, Ganesh R. Naik, Moran Gilat, James M. Shine, Tuan N. Nguyen, Quynh T Ly, Simon J.G. Lewis, Hung T. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Citations (Scopus)


Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson’s disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.

Original languageEnglish
Title of host publicationTelehealth for our Ageing Society - Selected Papers from Global Telehealth 2017
EditorsMaayken E.L. van den Berg, Anthony J. Maeder
Place of PublicationNetherlands
PublisherIOS PRESS
Number of pages8
ISBN (Electronic)9781614998440
Publication statusPublished - 2018
Externally publishedYes
Event2017 Global Telehealth Meeting, GT 201 - Adelaide, Australia
Duration: 24 Nov 2017 → …

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference2017 Global Telehealth Meeting, GT 201
Period24/11/17 → …


  • Brain effective connectivity
  • Electroencephalography
  • Freezing of gait
  • Movement disorder
  • Parkinson’s disease


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