ArticleDigital health
Validation of gait analysis using smartphones: Reliability and validity.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Clinical utility and methodological implementation of smartphone-based mobility analysis: a scoping review.Journal of neurology · 2026Article
- Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026Review
- Time-stratified daily walking speed measurement via smartphone and its predictive utility for mild cognitive impairment.Scientific reports · 2026Article
- Smartphone-Based Gait Assessment Captures Functional Recovery Following Total Knee Arthroplasty.Sensors (Basel, Switzerland) · 2026Article
- Gait Disturbances in Older Adults With Cerebral Small Vessel Disease: Mixed Methods Study Using Smartphone Sensors and Video Analysis.JMIR formative research · 2025Article
- Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations.Biosensors · 2025Article
- The Detection of Gait Events Based on Smartphones and Deep Learning.Bioengineering (Basel, Switzerland) · 2025Article
- Psychometric Characteristics of Smartphone-Based Gait Analyses in Chronic Health Conditions: A Systematic Review.Journal of functional morphology and kinesiology · 2025Review
- Automatic Detection of Gait Perturbations With Everyday Wearable Technology.IEEE open journal of engineering in medicine and biology · 2025Article
- Walk Longer! Using Wearable Inertial Sensors to Uncover Which Gait Aspects Should Be Treated to Increase Walking Endurance in People with Multiple Sclerosis.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aims to validate the reliability and validity of gait analysis using smartphones in a controlled environment. Methods: Thirty healthy adults attached smartphones to the waist and thigh, while an inertial measurement unit was fixed at the shank as a reference device; each participant was asked to walk six gait cycles at self-selected low, normal, and high speeds. Thirty-five cerebral small vessel disease patients were recruited to attach the smartphone to the thigh, performing single-task (ST), cognitive dual-task (DT Results: The results from the healthy group indicate that, regardless of whether attached to the thigh or waist, the smartphones calculated gait parameters with good reliability (ICC Conclusions: This study demonstrates the feasibility of using built-in smartphone sensors for gait analysis in a controlled environment.
Indexed as
Identifiers
What OpenQuestion holds
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.