Evidence map›Paper›PMID 35642200›Full record

ArticlePeerJ2022

Healthcare applications of single camera markerless motion capture: a scoping review.

Bradley Scott, Martin Seyres, Fraser Philp, Edward K Chadwick, Dimitra Blana

Open access · goldAbstract readScoping Review
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
13.0field-weighted citation impact, top 1% of its field
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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Markerless motion capture to quantify disability and functional performance in spine patients: a concurrent validity study bridging laboratory biomechanics and clinical practice.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
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  17. Aging With Artificial Intelligence: How Technology Enhances Older Adults' Health and Independence.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
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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

5 authors at 2 institutions in 1 country.

Bradley ScottSchool of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom.
Martin SeyresSchool of Engineering, University of Aberdeen, Aberdeen, United Kingdom.
Fraser PhilpSchool of Health Sciences, University of Liverpool, Liverpool, United Kingdom.
Edward K ChadwickSchool of Engineering, University of Aberdeen, Aberdeen, United Kingdom.
Dimitra BlanaSchool of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom.
University of Aberdeen · GBUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Single camera markerless motion capture has the potential to facilitate at home movement assessment due to the ease of setup, portability, and affordable cost of the technology. However, it is not clear what the current healthcare applications of single camera markerless motion capture are and what information is being collected that may be used to inform clinical decision making. This review aims to map the available literature to highlight potential use cases and identify the limitations of the technology for clinicians and researchers interested in the collection of movement data. Survey Methodology: Studies were collected up to 14 January 2022 using Pubmed, CINAHL and SPORTDiscus using a systematic search. Data recorded included the description of the markerless system, clinical outcome measures, and biomechanical data mapped to the International Classification of Functioning, Disability and Health Framework (ICF). Studies were grouped by patient population. Results: A total of 50 studies were included for data collection. Use cases for single camera markerless motion capture technology were identified for Neurological Injury in Children and Adults; Hereditary/Genetic Neuromuscular Disorders; Frailty; and Orthopaedic or Musculoskeletal groups. Single camera markerless systems were found to perform well in studies involving single plane measurements, such as in the analysis of infant general movements or spatiotemporal parameters of gait, when evaluated against 3D marker-based systems and a variety of clinical outcome measures. However, they were less capable than marker-based systems in studies requiring the tracking of detailed 3D kinematics or fine movements such as finger tracking. Conclusions: Single camera markerless motion capture offers great potential for extending the scope of movement analysis outside of laboratory settings in a practical way, but currently suffers from a lack of accuracy where detailed 3D kinematics are required for clinical decision making. Future work should therefore focus on improving tracking accuracy of movements that are out of plane relative to the camera orientation or affected by occlusion, such as supination and pronation of the forearm.

Indexed as

Motion CaptureMovementAdultChildDelivery of Health CareGaitHumansSurveys and QuestionnairesClinical motion captureMarkerlessMarkerless motion captureMusculoskeletalNeurological injuriesScoping reviewSingle camera human motion analysisSingle camera markerless motion captureSingle camera movement analysis of humansTelerehabilitation

Identifiers

PMID35642200
PMCPMC9148557
OpenAlexW4281568353

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.