Evidence map›Paper›PMID 42358744›Full record

ArticleDigital biomarkers

Impact of Video Quality on Video-Based Digital Assessment of Parkinson's Disease.

Atefeh Irani, Kye Won Park, Maryam S Mirian, Mahdi Shakouri, Michael Grundy, Juana Ayala, Reshad Hosseini, Hadi Moradi, Martin J McKeown

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In one paragraph

Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Atefeh IraniPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.
Kye Won ParkPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.
Maryam S MirianPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.
Mahdi ShakouriPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.
Michael GrundyPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.
Juana AyalaPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.
Reshad HosseiniSchool of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
Hadi MoradiSchool of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
Martin J McKeownPacific Parkinson Research Centre, University of British Columbia, Vancouver, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Vision-based digital biomarkers have emerged as promising tools for objectively (and possibly remotely) assessing Parkinson's disease (PD) motor signs, addressing inherent limitations of traditional clinical scales like the Unified Parkinson's Disease Rating Scale (UPDRS). However, real-world deployment is hindered by variability in video quality, particularly in uncontrolled home environments. This study aims to quantify the impact of video quality parameters on the accuracy of human pose estimation (HPE) and downstream clinical assessments, including finger-tapping event detection and UPDRS scoring. Methods: We analyzed videos of PD patients performing finger-tapping tasks across two settings: high-resolution recordings collected in controlled clinical environments ( Results: Low frame rates and inadequate hand coverage within the frame significantly reduced the accuracy of HPE-based assessments. In contrast, video resolution had a less pronounced effect than expected. Conclusion: Frame rate and proper visibility of body parts are more critical than resolution for reliable at-home motor signs evaluation in PD. We establish practical thresholds for video quality in remote PD assessments and provide actionable guidelines for optimizing remote monitoring systems.

Indexed as

Clinical video processingFinger tappingParkinson’s diseaseRemote monitoringVideo quality assessment

Identifiers

PMID42358744
PMCPMC13293597

What OpenQuestion holds

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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.