Currently submitted to: Journal of Medical Internet Research
Date Submitted: Feb 17, 2026
Open Peer Review Period: Feb 18, 2026 - Apr 15, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Wearable sensors in gait assessment for Parkinson’s disease and stroke in real-world environments: a rapid review and meta-analysis
ABSTRACT
Background:
Real-world gait assessment has gained momentum in populations with walking impairments, offering insights beyond standardized tests and supporting the integration of remote monitoring into clinical care. However, the full potential of wearable sensors remains limited by the lack of validated population- and context-specific digital biomarkers.
Objective:
The primary objective was to update the state of the art and summarize challenges in real-world gait assessment for PD and stroke. The secondary objective was to report pooled means and standard deviations of gait parameters.
Methods:
PubMed and Scopus were searched for English-language studies published up to December 31, 2024. Eligible studies included a minimum of five individuals with Parkinson’s disease (PD) or post-stroke and used wearable sensors to assess gait in real-world settings. Studies conducted solely in laboratory or rehabilitation environments, non-peer-reviewed articles, abstracts, or studies before 2014 were excluded.
Results:
Of 167 records identified, 34 studies were included, comprising 30 on PD (n=209; 812 [37%] female, 1359 [63%] male, mean age 68,59 years [SD 7,86]) and four on stroke (n=159; 77 [49%] female, 80 [51%] male, mean age 64,16 years [SD 10,51]). The meta-analysis for PD covered seven gait parameters with high heterogeneity across outcomes (I²>97%).
Conclusions:
Wearable sensors show strong potential for real-world gait assessment, but inconsistent methods call for standardization in sensor placement, algorithm validation, and metric definitions. Stroke populations are underrepresented, highlighting the need for targeted validation. Clinical Trial: This rapid review and meta-analysis was registered with PROSPERO, CRD42024531665.
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