ArticleSensors (Basel, Switzerland)2024
Comparison of Shoulder Range of Motion Quantified with Mobile Phone Video-Based Skeletal Tracking and 3D Motion Capture-Preliminary Study.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06629038 (A Novel Technique for Estimating Maximal Jaw Movement, Neck and Shoulder Joint Range of Motion Using an Artificial Intelligence Model), which is not on this map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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.
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.
A Novel Technique for Estimating Maximal Jaw Movement, Neck and Shoulder Joint Range of Motion Using an Artificial Intelligence Model
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of the quantitative assessment of lower extremity motor function in elderly individuals based on objective detection.Journal of neuroengineering and rehabilitation · 2024Pooled it
- Tele-Rehabilitation and Tele-Diagnostics in Shoulder Disorders: Current Evidence, Challenges, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Evaluation of Smartphone Camera Positioning on Artificial Intelligence Pose Estimation Accuracy for Exercise Detection: Observational Study.JMIR mHealth and uHealth · 2026Observational
- Video-Based Motion Capture Smartphone Apps for Testing Human Motor Performance Skills: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Psychometric Properties of a Smartphone Application for Measuring Shoulder Active Range of Motion in Individuals with and without Shoulder Pain and Mobility Deficits.Journal of pain research · 2026Article
- How do visual and smartphone camera-based shoulder ranges of motion compare?JSES international · 2025Article
- The Future of Clinical Active Shoulder Range of Motion Assessment, Best Practice, and Its Challenges: Narrative Review.Sensors (Basel, Switzerland) · 2025Review
- Application of deep learning for diagnosis of shoulder diseases in older adults: a narrative review.Ewha medical journal · 2025Review
- Rheumatology in the digital health era: status quo and quo vadis?Nature reviews. Rheumatology · 2024Review
- A Video App for Screening Osgood-Schlatter Disease Using Soccer Instep Kicking Motion Analysis.Cureus · 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
Abstract
backgroundThe accuracy of human pose tracking using smartphone camera (2D-pose) to quantify shoulder range of motion (RoM) is not determined.
methodsTwenty healthy individuals were recruited and performed shoulder abduction, adduction, flexion, or extension, captured simultaneously using a smartphone-based human pose estimation algorithm (Apple's vision framework) and using a skin marker-based 3D motion capture system. Validity was assessed by comparing the 2D-pose outcomes against a well-established 3D motion capture protocol. In addition, the impact of iPhone positioning was investigated using three smartphones in multiple vertical and horizontal positions. The relationship and validity were analysed using linear mixed models and Bland-Altman analysis.
resultsWe found that 2D-pose-based shoulder RoM was consistent with 3D motion capture (linear mixed model: R
conclusionsShoulder RoM estimated using a smartphone camera is consistent with 3D motion-capture-derived RoM; however, differences between the systems were observed and are likely explained by differences in thoracic frame definitions.
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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.