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Quantifying soft tissue artefacts and imaging variability in motion capture of the fingers

Quantifying soft tissue artefacts and imaging variability in motion capture of the fingers
Quantifying soft tissue artefacts and imaging variability in motion capture of the fingers
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 were aligned and 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 RMSEs 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. 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.
Biomechanical modelling, CT, Hand, Kinematic, MoCap, Musculoskeletal, STA, Skin movement artefact
0090-6964
1551-1561
Metcalf, C.D.
09a47264-8bd5-43bd-a93e-177992c22c72
Phillips, C.
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Forrester, A.
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Glodowski, J.
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Simpson, K.
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Everitt, C.
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Darekar, A.
314a85df-6c85-43e1-8312-9b7616a54cc7
King, L.
7442bd3c-ed4c-46aa-9d9b-1898a113c740
Warwick, D.
f6d42a53-1af3-44f9-9741-5268e95c2b7e
Dickinson, A.S.
10151972-c1b5-4f7d-bc12-6482b5870cad
Metcalf, C.D.
09a47264-8bd5-43bd-a93e-177992c22c72
Phillips, C.
64d39da7-ce38-4265-9c8e-6c20c9ce4bba
Forrester, A.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
Glodowski, J.
778bef04-8391-452d-9dbc-5d104c02f074
Simpson, K.
d5cfb9cb-c945-4ebb-b6a2-99139abf3750
Everitt, C.
62cd944b-84a2-441e-bab7-1e85e9156bcf
Darekar, A.
314a85df-6c85-43e1-8312-9b7616a54cc7
King, L.
7442bd3c-ed4c-46aa-9d9b-1898a113c740
Warwick, D.
f6d42a53-1af3-44f9-9741-5268e95c2b7e
Dickinson, A.S.
10151972-c1b5-4f7d-bc12-6482b5870cad

Metcalf, C.D., Phillips, C., Forrester, A., Glodowski, J., Simpson, K., Everitt, C., Darekar, A., King, L., Warwick, D. and Dickinson, A.S. (2020) Quantifying soft tissue artefacts and imaging variability in motion capture of the fingers. Annals of Biomedical Engineering, 48 (5), 1551-1561. (doi:10.1007/s10439-020-02476-2).

Record type: Article

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 were aligned and 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 RMSEs 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. 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.

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Metcalf 2020 Article Quantifying Soft Tissue Artefacts - Version of Record
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More information

Submitted date: 30 October 2019
Accepted/In Press date: 5 February 2020
e-pub ahead of print date: 19 February 2020
Keywords: Biomechanical modelling, CT, Hand, Kinematic, MoCap, Musculoskeletal, STA, Skin movement artefact

Identifiers

Local EPrints ID: 438210
URI: http://eprints.soton.ac.uk/id/eprint/438210
ISSN: 0090-6964
PURE UUID: 404b8041-e2f6-450d-911a-275ed09c742a
ORCID for C.D. Metcalf: ORCID iD orcid.org/0000-0002-7404-6066
ORCID for C. Phillips: ORCID iD orcid.org/0000-0002-6315-474X
ORCID for A.S. Dickinson: ORCID iD orcid.org/0000-0002-9647-1944

Catalogue record

Date deposited: 04 Mar 2020 17:31
Last modified: 26 Nov 2021 02:51

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Contributors

Author: C.D. Metcalf ORCID iD
Author: C. Phillips ORCID iD
Author: A. Forrester
Author: J. Glodowski
Author: K. Simpson
Author: C. Everitt
Author: A. Darekar
Author: L. King
Author: D. Warwick
Author: A.S. Dickinson ORCID iD

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