ArticleNeurology2016
Objective, computerized video-based rating of blepharospasm severity.
Article in Neurology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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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
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Computer Vision Technologies in Movement Disorders: A Systematic Review.Movement disorders clinical practice · 2025Pooled it
- An Exploratory, Randomized, Double-Blind Clinical Trial of Dipraglurant for Blepharospasm.Movement disorders : official journal of the Movement Disorder Society · 2024Trial
- Smartphone video-based early diagnosis of blepharospasm using dual cross-attention modeling enhanced by facial pose estimation.NPJ digital medicine · 2025Article
- Motor assessment of X-linked dystonia parkinsonism via machine-learning-based analysis of wearable sensor data.Scientific reports · 2024Article
- Interrater reliability of motor severity scales for hemifacial spasm.Journal of neural transmission (Vienna, Austria : 1996) · 2023Article
- Quantitative evaluation of blinking in blepharospasm using electrooculogram-integrated smart eyeglasses.Scientific reports · 2023Article
- Hold that pose: capturing cervical dystonia's head deviation severity from video.Annals of clinical and translational neurology · 2022Article
- New modalities and directions for dystonia care.Journal of neural transmission (Vienna, Austria : 1996) · 2021Review
- The Dystonia Coalition: A Multicenter Network for Clinical and Translational Studies.Frontiers in neurology · 2021Review
- Sensorimotor simulation and emotion processing: Impairing facial action increases semantic retrieval demands.Cognitive, affective & behavioral neuroscience · 2017Article
- A Dynamic Circuit Hypothesis for the Pathogenesis of Blepharospasm.Frontiers in computational neuroscience · 2017Article
- Facial artificial intelligence in ophthalmology and medicine: fundamental and transformative applications.Therapeutic advances in ophthalmologyReview
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 2 countries.
Funding
Abstract
objectiveTo compare clinical rating scales of blepharospasm severity with involuntary eye closures measured automatically from patient videos with contemporary facial expression software.
methodsWe evaluated video recordings of a standardized clinical examination from 50 patients with blepharospasm in the Dystonia Coalition's Natural History and Biorepository study. Eye closures were measured on a frame-by-frame basis with software known as the Computer Expression Recognition Toolbox (CERT). The proportion of eye closure time was compared with 3 commonly used clinical rating scales: the Burke-Fahn-Marsden Dystonia Rating Scale, Global Dystonia Rating Scale, and Jankovic Rating Scale.
resultsCERT was reliably able to find the face, and its eye closure measure was correlated with all of the clinical severity ratings (Spearman ρ = 0.56, 0.52, and 0.56 for the Burke-Fahn-Marsden Dystonia Rating Scale, Global Dystonia Rating Scale, and Jankovic Rating Scale, respectively, all p < 0.0001).
conclusionsThe results demonstrate that CERT has convergent validity with conventional clinical rating scales and can be used with video recordings to measure blepharospasm symptom severity automatically and objectively. Unlike EMG and kinematics, CERT requires only conventional video recordings and can therefore be more easily adopted for use in the clinic.
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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.