Smartphone videos are a scalable tool for gait evaluation in Parkinson’s disease

Han et al. show that deep learning applied to simple smartphone videos can match specialist ratings of gait impairment, detect medication effects, and surface novel movement features as candidate biomarkers in Parkinson’s disease. These steps toward remote, objective gait assessment complement advances in wearable-powered symptom tracking and promise extended access to care alongside enriched clinical trial metrics. To realize these benefits, implementation research focused on validating care models is needed.

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Publication Details

Journal
npj Digital Medicine
Published
2026-02-16
DOI
https://doi.org/10.1038/s41746-026-02447-2
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
0.00
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article

Smartphone videos are a scalable tool for gait evaluation in Parkinson’s disease

Joseph C. Kvedar, Kyra L. Rosen, Margaret Sui
npj Digital Medicine
Balance, Gait, and Falls Prevention
article

Smartphone videos are a scalable tool for gait evaluation in Parkinson’s disease

Joseph C. Kvedar, Kyra L. Rosen, Margaret Sui
article en

Abstract

Han et al. show that deep learning applied to simple smartphone videos can match specialist ratings of gait impairment, detect medication effects, and surface novel movement features as candidate biomarkers in Parkinson’s disease. These steps toward remote, objective gait assessment complement advances in wearable-powered symptom tracking and promise extended access to care alongside enriched clinical trial metrics. To realize these benefits, implementation research focused on validating care models is needed.

npj Digital MedicineVol. 9(1)
Harvard University (US), Dana-Farber Cancer Institute (US)
Openalex Percentile: Top 56%
Balance, Gait, and Falls Prevention
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