amsys 16(10): e4

Research Article

Gait Parameters Change Prior to Freezing in Parkinson's Disease: A Data-Driven Study with Wearable Inertial Units

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  • @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
Maria Laura Ferster1, Sinziana Mazilu1,*, Gerhard Tröster1
  • 1: ETH Zurich
*Contact email: sinziana.mazilu@ife.ee.ethz.ch

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.