ArticleParkinsonism & related disorders2022
Understanding how people with Parkinson's disease turn in gait from a real-world in-home dataset.
Article in Parkinsonism & related disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Impact of dual-tasking and balance confidence on turns and transitions: a cross-sectional study in Parkinson's disease.Scientific reports · 2026Article
- Your turn: At home turning angle estimation for Parkinson's disease severity assessment.Artificial intelligence in medicine · 2025Article
- Association Between Turn Impairments and Cognitive Function in Parkinson Disease.Aging medicine (Milton (N.S.W)) · 2025Article
- Spatiotemporal Gait Parameters During Turning and Imbalance in Parkinson's Disease: Video-Based Analysis From a Single Camera.Journal of movement disorders · 2025Article
- Cognition and Activity of Daily Living Function in people with Parkinson's disease.Journal of neural transmission (Vienna, Austria : 1996) · 2024Review
- A multimodal dataset of real world mobility activities in Parkinson's disease.Scientific data · 2023Article
- Automated Real-World Video Analysis of Sit-to-Stand Transitions Predicts Parkinson's Disease Severity.Digital biomarkersArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
introductionTurning in gait digital parameters may be useful in measuring disease progression in Parkinson's disease (PD), however challenges remain over algorithm validation in real-world settings. The influence of clinician observation on turning outcomes is poorly understood. Our objective is to describe a unique in-home video dataset and explore the use of turning parameters as biomarkers in PD.
methods11 participants with PD, 11 control participants stayed in a home-like setting living freely for 5 days (with two sessions of clinical assessment), during which high-resolution video was captured. Clinicians watched the videos, identified turns and documented turning parameters.
resultsFrom 85 hours of video 3869 turns were evaluated, averaging at 22.7 turns per hour per person. 6 participants had significantly different numbers of turning steps and/or turn duration between "ON" and "OFF" medication states. Positive Spearman correlations were seen between the Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale III score with a) number of turning steps (rho = 0.893, p < 0.001), and b) duration of turn (rho = 0.744, p = 0.009) "OFF" medications. A positive correlation was seen "ON" medications between number of turning steps and clinical rating scale score (rho = 0.618, p = 0.048). Both cohorts took more steps and shorter durations of turn during observed clinical assessments than when free-living.
conclusionThis study shows proof of concept that real-world free-living turn duration and number of turning steps recorded can distinguish between PD medication states and correlate with gold-standard clinical rating scale scores. It illustrates a methodology for ecological validation of real-world digital outcomes.
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