ArticleJournal of the neurological sciences2022
Head tremor in cervical dystonia: Quantifying severity with computer vision.
Article in Journal of the neurological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
What it found
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.
- Computer Vision Technologies in Movement Disorders: A Systematic Review.Movement disorders clinical practice · 2025Pooled it
- A systematic review of the applications of markerless motion capture (MMC) technology for clinical measurement in rehabilitation.Journal of neuroengineering and rehabilitation · 2023Pooled it
- The Influence of Videography in the Foundation and Future of Movement Disorders.Movement disorders clinical practice · 2026Review
- Abnormal head movements in neurological conditions: a knowledge-based dataset with application to cervical dystonia.Frontiers in digital health · 2026Article
- Video-Based Data-Driven Models for Diagnosing Movement Disorders: Review and Future Directions.Movement disorders : official journal of the Movement Disorder Society · 2025Review
- Artificial Intelligence in the Diagnosis and Quantitative Phenotyping of Hyperkinetic Movement Disorders: A Systematic Review.Journal of clinical medicine · 2024Review
- Head movement dynamics in dystonia: a multi-centre retrospective study using visual perceptive deep learning.NPJ digital medicine · 2024Article
- Hold that pose: capturing cervical dystonia's head deviation severity from video.Annals of clinical and translational neurology · 2022Article
- From null to midline: changes in head posture do not predictably change head tremor in cervical dystonia.Dystonia (Lausanne, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
18 authors at 9 institutions in 1 country.
Funding
Abstract
backgroundHead tremor (HT) is a common feature of cervical dystonia (CD), usually quantified by subjective observation. Technological developments offer alternatives for measuring HT severity that are objective and amenable to automation.
objectivesOur objectives were to develop CMOR (Computational Motor Objective Rater; a computer vision-based software system) to quantify oscillatory and directional aspects of HT from video recordings during a clinical examination and to test its convergent validity with clinical rating scales.
methodsFor 93 participants with isolated CD and HT enrolled by the Dystonia Coalition, we analyzed video recordings from an examination segment in which participants were instructed to let their head drift to its most comfortable dystonic position. We evaluated peak power, frequency, and directional dominance, and used Spearman's correlation to measure the agreement between CMOR and clinical ratings.
resultsPower averaged 0.90 (SD 1.80) deg
conclusionsWe demonstrate a new objective method to measure HT severity that requires only conventional video recordings, quantifies the complexities of HT in CD, and exhibits convergent validity with clinical severity ratings.
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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.