Research Article
Gait Parameters Change Prior to Freezing in Parkinson's Disease: A Data-Driven Study with Wearable Inertial Units
@ARTICLE{10.4108/eai.28-9-2015.2261411, author={Maria Laura Ferster and Sinziana Mazilu and Gerhard Tr\o{}ster}, title={Gait Parameters Change Prior to Freezing in Parkinson's Disease: A Data-Driven Study with Wearable Inertial Units}, journal={EAI Endorsed Transactions on Ambient Systems}, volume={3}, number={10}, publisher={EAI}, journal_a={AMSYS}, year={2015}, month={12}, keywords={prediction, wearable sensors, freezing of gait, parkinson's disease, gait parameters, motor impairment analysis}, doi={10.4108/eai.28-9-2015.2261411} }
- Maria Laura Ferster
Sinziana Mazilu
Gerhard Tröster
Year: 2015
Gait Parameters Change Prior to Freezing in Parkinson's Disease: A Data-Driven Study with Wearable Inertial Units
AMSYS
EAI
DOI: 10.4108/eai.28-9-2015.2261411
Abstract
Freezing of gait (FoG) is a motor impairment among patients with advanced Parkinson's disease which is associated with falls and has a negative impact on a patient's quality of life. Wearable systems have been developed to detect FoG and to help patients resume walking by means of rhythmical cueing. A step further is to predict the FoG and start cueing a few seconds before it happens, which might help patients avoid the gait freeze entirely. We characterize the gait parameters continuously with up to 10-12 seconds prior to FoG, observe if and how they change before subjects enter FoG, and compare them with the gait before turns. Moreover, we introduce and discuss new frequency-based features to describe gait and motor anomalies prior to FoG. Using inertial units mounted on the ankles of 5 subjects, we show specific changes in the stride duration and length with up to four seconds prior to FoG on all subjects, compared with turns. Moreover, the dominant frequency migrates towards [3, 8] Hz band with up to six seconds prior to FoG on 3 subjects. These findings open the path to real-time prediction of FoG from inertial measurement units.
Copyright © 2015 S. Mazilu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.