ArticleFrontiers in neurology2025
Diagnostic utility of smartphone-integrated gait analysis in the assessment of BPPV.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed.
- Clinical utility and methodological implementation of smartphone-based mobility analysis: a scoping review.Journal of neurology · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Benign Paroxysmal Positional Vertigo (BPPV) is the most common vestibular disorder causing gait disturbances. Smartphone-based gait analysis has emerged as a portable, cost-effective alternative to laboratory-based assessments. Objective: To evaluate the diagnostic utility of smartphone-based gait analysis in BPPV patients and its effectiveness in assessing treatment outcomes following canalith repositioning maneuvers. Methods: This prospective case-control study included 26 patients with posterior canal BPPV and 37 demographically matched healthy controls. Gait analysis was performed using a smartphone application with participants walking 25 meters at a self-selected pace. In the BPPV group, measurements were repeated after Epley maneuver. Patient-reported outcomes were assessed using the Vertigo Symptom Scale (VSS), Vertigo Dizziness Imbalance Symptom Scale (VDI-SS), and Health Related Quality of Life (VDI -HRQoL). Results: Compared to controls, BPPV patients demonstrated significantly fewer steps (31.31 ± 6.07 vs. 27.73 ± 6.52, Conclusion: Smartphone-based gait analysis can identify characteristic gait abnormalities in BPPV patients, suggesting its potential as a complementary diagnostic tool. However, it appears less sensitive for detecting early post-treatment biomechanical changes despite symptomatic improvement. Further validation studies with larger samples and extended follow-up periods are warranted.
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