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Published (Version of Record)CC BY V4.0, Open Access
Journal article
Gait analysis with wearables predicts conversion to Parkinson disease
Annals of Neurology, Vol.86(3), pp.357-367
2019
Abstract
Objective
Quantification of gait with wearable technology is promising; recent cross-sectional studies showed that gait characteristics are potential prodromal markers for Parkinson disease (PD). The aim of this longitudinal prospective observational study was to establish gait impairments and trajectories in the prodromal phase of PD, identifying which gait characteristics are potentially early diagnostic markers of PD.
Methods
The 696 healthy controls (mean age = 63 ± 7 years) recruited in the Tubingen Evaluation of Risk Factors for Early Detection of Neurodegeneration study were included. Assessments were performed longitudinally 4 times at 2-year intervals, and people who converted to PD were identified. Participants were asked to walk at different speeds under single and dual tasking, with a wearable device placed on the lower back; 14 validated clinically relevant gait characteristics were quantified. Cox regression was used to examine whether gait at first visit could predict time to PD conversion after controlling for age and sex. Random effects linear mixed models (RELMs) were used to establish longitudinal trajectories of gait and model the latency between impaired gait and PD diagnosis.
Results
Sixteen participants were diagnosed with PD on average 4.5 years after first visit (converters; PDC). Higher step time variability and asymmetry of all gait characteristics were associated with a shorter time to PD diagnosis. RELMs indicated that gait (lower pace) deviates from that of non-PDC approximately 4 years prior to diagnosis.
Interpretation
Together with other prodromal markers, quantitative gait characteristics can play an important role in identifying prodromal PD and progression within this phase. ANN NEUROL 2019;86:357–367
Details
- Title
- Gait analysis with wearables predicts conversion to Parkinson disease
- Authors/Creators
- S. Del Din (Author/Creator) - Newcastle UniversityM. Elshehabi (Author/Creator) - University Hospital Schleswig-HolsteinB. Galna (Author/Creator) - Newcastle UniversityM.A. Hobert (Author/Creator) - University Hospital Schleswig-HolsteinE. Warmerdam (Author/Creator) - University Hospital Schleswig-HolsteinU. Suenkel (Author/Creator) - Center for Neurology and Hertie Institute for Clinical Brain Research, Department of Neurodegenerative Diseases, University Hospital Tübingen, and Center for Neurodegenerative Diseases, Tübingen, Germany.K. Brockmann (Author/Creator) - Center for Neurology and Hertie Institute for Clinical Brain Research, Department of Neurodegenerative Diseases, University Hospital Tübingen, and Center for Neurodegenerative Diseases, Tübingen, Germany.F. Metzger (Author/Creator) - University of TübingenC. Hansen (Author/Creator) - University Hospital Schleswig-HolsteinD. Berg (Author/Creator) - University Hospital Schleswig-HolsteinL. Rochester (Author/Creator) - Newcastle UniversityW. Maetzler (Author/Creator) - University Hospital Schleswig-Holstein
- Publication Details
- Annals of Neurology, Vol.86(3), pp.357-367
- Publisher
- Wiley Periodicals, Inc. on behalf of American Neurological Association
- Identifiers
- 991005542488207891
- Copyright
- © 2019 The Authors
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.82 Gait & Posture
- 1.82.263 Gait and Balance
- Web Of Science research areas
- Clinical Neurology
- Neurosciences
- ESI research areas
- Neuroscience & Behavior