ArticleJournal of neurology2026
Clinical utility and methodological implementation of smartphone-based mobility analysis: a scoping review.
Article in Journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
backgroundMobility is an informative marker of neurological function, physiological reserve, and functional independence. Laboratory gait analysis requires costly specialized equipment, while research wearables can impose sustained-use burdens. Smartphone inertial measurement units (IMUs) offer a widely available platform for longitudinal assessment within a patient's natural environment.
methodsFollowing PRISMA-ScR guidelines, PubMed, Embase, and Scopus were searched for peer-reviewed studies using internal smartphone sensors to map reported clinical applications, methodological implementation, validation approaches, and translational barriers.
resultsEighty-four studies met the inclusion criteria. Neurology was the most frequently represented clinical domain (36.9%), with additional applications in geriatrics (14.3%) and orthopedics (13.1%). 10.7% (n=9) were classified as validation-focused; the remainder had diagnostic (36.9%), prognostic (38.1%), or longitudinal monitoring (14.3%) aims. Most assessments remained controlled (54.8%), supervised (67.9%), and dependent on active testing protocol (73.8%), whereas only 23.8% captured passive, free-living mobility. Implementation was heterogeneous: 71.4% of protocols required fixed device placements, 82.1% used custom software, and 7.1% integrated with native platforms. The extracted measures included activity volume, gait-quality metrics, and machine-learning features derived from raw inertial data.
conclusionSmartphones provide a widely available platform for multidimensional mobility sensing, but the mapped evidence largely concerns feasibility, technical validation, or associations with clinical status and outcomes. Routine clinical utility has not been established. Translation will require standardized acquisition and reporting, cross-device and cross-platform validation, context-aware analysis, privacy-preserving data governance, and prospective evidence that implementation improves clinical decisions or patient-relevant outcomes. Passive monitoring may complement standardized assessment by providing longitudinal measures of real-world performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.