Evidence map›Paper›PMID 32076882›Full record

ArticleAnnals of biomedical engineering2020

Quantifying Soft Tissue Artefacts and Imaging Variability in Motion Capture of the Fingers.

C D Metcalf, C Phillips, A Forrester, J Glodowski, K Simpson, C Everitt, A Darekar, L King, D Warwick, A S Dickinson

Open access · hybridAbstract read
In one paragraph

Article in Annals of biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Biomechanical Characterization of Metacarpal Fixation: Internal Load Determination and Evaluation of a Novel Adhesive Osteosynthesis.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025
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  7. Lumbar segment-dependent soft tissue artifacts of skin markers duringFrontiers in bioengineering and biotechnology · 2022
    Article
  8. Article
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

10 authors at 2 institutions in 1 country.

C D MetcalfFaculty of Environmental & Life Sciences, University of Southampton, Southampton, UK.
C PhillipsFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.
A ForresterFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.
J GlodowskiFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.
K SimpsonFaculty of Environmental & Life Sciences, University of Southampton, Southampton, UK.
C EverittUniversity Hospital Southampton, Southampton, UK.
A DarekarUniversity Hospital Southampton, Southampton, UK.
L KingUniversity Hospital Southampton, Southampton, UK.
D WarwickUniversity Hospital Southampton, Southampton, UK.
A S DickinsonFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK. alex.dickinson@soton.ac.uk.ORCID http://orcid.org/0000-0002-9647-1944
University of Southampton · GBUniversity Hospital Southampton NHS Foundation Trust · GB

Funding

Engineering and Physical Sciences Research Council EP/L505067/1Engineering and Physical Sciences Research Council EP/N509747/1Royal Academy of Engineering (UK) RF/130
6 · The paper itself

Abstract

This study assessed the accuracy of marker-based kinematic analysis of the fingers, considering soft tissue artefacts (STA) and marker imaging uncertainty. We collected CT images of the hand from healthy volunteers with fingers in full extension, mid- and full-flexion, including motion capture markers. Bones and markers were segmented and meshed. The bone meshes for each volunteer's scans were aligned using the proximal phalanx to study the proximal interphalangeal joint (PIP), and using the middle phalanx to study the distal interphalangeal joint (DIP). The angle changes between positions were extracted. The HAWK protocol was used to calculate PIP and DIP joint flexion angles in each position based on the marker centroids. Finally the marker locations were 'corrected' relative to the underlying bones, and the flexion angles recalculated. Static and dynamic marker imaging uncertainty was evaluated using a wand. A strong positive correlation was observed between marker- and CT-based joint angle changes with 0.980 and 0.892 regression slopes for PIP and DIP, respectively, and Root Mean Squared Errors below 4°. Notably for the PIP joint, correlation was worsened by STA correction. The 95% imaging uncertainty interval was < ± 1° for joints, and < ± 0.25 mm for segment lengths. In summary, the HAWK marker set's accuracy was characterised for finger joint flexion angle changes in a small group of healthy individuals and static poses, and was found to benefit from skin movements during flexion.

Indexed as

ArtifactsAdultBiomechanical PhenomenaFemaleFinger JointFingersHumansMaleMotionSkinSkin Physiological PhenomenaTomography, X-Ray ComputedBiomechanical modellingCTHandKinematicMoCapMusculoskeletalSkin movement artefactSTA

Identifiers

PMID32076882
PMCPMC7154021
OpenAlexW3008267370

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.