ArticleScientific reports2025
Validity of tremor analysis using smartphone compatible computer vision frameworks.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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Who cites it
6 citing papers in PubMed.
- Enhancing mobile brain and body imaging: Open-source solutions for real-world research applications.iScience · 2026Article
- A portable solution for simultaneous human movement and mobile EEG acquisition: readiness potential for basketball free-throw shooting.Experimental brain research · 2026Article
- Digital diagnostics, biomarkers and therapeutics in an evolving healthcare system: From promise to practice.British journal of clinical pharmacology · 2026Review
- Essential Tremor and Digital Biomarkers: A Scoping Review Using the TRACE Framework to Map Readiness for Clinical Trials and Routine Practice.Tremor and other hyperkinetic movements (New York, N.Y.) · 2026Article
- Video-based quantification of hand postural tremor without external references. Integrating postural tremor quantification into visionMD.NPJ Parkinson's disease · 2025Article
- Botulinum Toxin for the Treatment of Tremors.Toxins · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer vision (CV)-based approaches hold promising potential for the classification and quantitative assessment of movement disorders. To take full advantage of this potential, the pipelines need to be validated against established clinical and electrophysiological gold standards. This study examines the validity of the Mediapipe (by Google) and Vision (by Apple) smartphone-enabled hand detection frameworks for tremor analysis. Both frameworks were tested in virtual experiments with simulated tremulous hands to determine the optimal camera position for hand tremor assessment and the minimum detectable tremor amplitude and frequency. Both frameworks were then compared with optical motion capture (OMC), accelerometry, and clinical ratings in 20 tremor patients. Both CV frameworks accurately measured tremor peak frequency. Significant correlations were found between CV-assessed tremor amplitudes and Essential Tremor Rating Assessment Scale (TETRAS) scores. However, the accuracy of amplitude estimation compared to OMC as ground truth was insufficient for clinical application. In conclusion, CV-based tremor analysis is an accurate and simple clinical assessment tool to determine tremor frequency. Further improvements in amplitude estimation are needed.
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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.