Evidence map›Paper›PMID 36707523›Full record

ArticleNPJ Parkinson's disease2023

Computer vision quantification of whole-body Parkinsonian bradykinesia using a large multi-site population.

Gareth Morinan, Yuriy Dushin, Grzegorz Sarapata, Samuel Rupprechter, Yuwei Peng, Christine Girges, Maricel Salazar, Catherine Milabo, Krista Sibley, Thomas Foltynie and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ Parkinson's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  16. Video-Based Data-Driven Models for Diagnosing Movement Disorders: Review and Future Directions.Movement disorders : official journal of the Movement Disorder Society · 2025
    Review
  17. Observational
  18. [Research progress in motor assessment of neurodegenerative diseases driven by motion capture data].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Gareth Morinan *Machine Medicine Technologies Ltd., The Leather Market Unit 1.1.1 11/13 Weston Street, London, SE1 3ER, UK.ORCID http://orcid.org/0000-0001-9727-5630
Yuriy Dushin *Machine Medicine Technologies Ltd., The Leather Market Unit 1.1.1 11/13 Weston Street, London, SE1 3ER, UK. yuriy@machinemedicine.com.ORCID http://orcid.org/0000-0002-6060-299X
Grzegorz SarapataMachine Medicine Technologies Ltd., The Leather Market Unit 1.1.1 11/13 Weston Street, London, SE1 3ER, UK.ORCID http://orcid.org/0000-0001-9021-6232
Samuel RupprechterMachine Medicine Technologies Ltd., The Leather Market Unit 1.1.1 11/13 Weston Street, London, SE1 3ER, UK.
Yuwei PengMachine Medicine Technologies Ltd., The Leather Market Unit 1.1.1 11/13 Weston Street, London, SE1 3ER, UK.
Christine GirgesDepartment of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
Maricel SalazarDepartment of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
Catherine MilaboDepartment of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
Krista SibleyDepartment of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
Thomas FoltynieDepartment of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.ORCID http://orcid.org/0000-0003-0752-1813
Ioana CociasuNeuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK.ORCID http://orcid.org/0000-0003-0232-6509
Lucia RicciardiNeuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK.
Fahd BaigNeuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK.ORCID http://orcid.org/0000-0002-3315-2698
Francesca MorganteNeuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK.
Louise-Ann LeylandDementia Research Center, Institute of Neurology, University College London, Queen Square, London, WC1N 3AR, UK.
Rimona S WeilDementia Research Center, Institute of Neurology, University College London, Queen Square, London, WC1N 3AR, UK.ORCID http://orcid.org/0000-0002-5092-6325
Ro'ee GilronThe Starr Lab, University of California San Francisco, 513 Parnassus Ave, HSE-823, San Francisco, CA, 94143, USA.
Jonathan O'KeeffeMachine Medicine Technologies Ltd., The Leather Market Unit 1.1.1 11/13 Weston Street, London, SE1 3ER, UK. jonathan@machinemedicine.com.

Funding

Wellcome Trust 205167/Z/16/Z
6 · The paper itself

Abstract

Parkinson's disease (PD) is a common neurological disorder, with bradykinesia being one of its cardinal features. Objective quantification of bradykinesia using computer vision has the potential to standardise decision-making, for patient treatment and clinical trials, while facilitating remote assessment. We utilised a dataset of part-3 MDS-UPDRS motor assessments, collected at four independent clinical and one research sites on two continents, to build computer-vision-based models capable of inferring the correct severity rating robustly and consistently across all identifiable subgroups of patients. These results contrast with previous work limited by small sample sizes and small numbers of sites. Our bradykinesia estimation corresponded well with clinician ratings (interclass correlation 0.74). This agreement was consistent across four clinical sites. This result demonstrates how such technology can be successfully deployed into existing clinical workflows, with consumer-grade smartphone or tablet devices, adding minimal equipment cost and time.

Identifiers

PMID36707523
PMCPMC9883391

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.