Evidence map›Paper›PMID 38903187›Full record

ArticleFrontiers in bioengineering and biotechnology2024

Determination of muscle shape deformations of the tibialis anterior during dynamic contractions using 3D ultrasound.

Annika S Sahrmann, Lukas Vosse, Tobias Siebert, Geoffrey G Handsfield, Oliver Röhrle

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Article in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Annika S SahrmannInstitute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.
Lukas VosseStuttgart Center for Simulation Science, University of Stuttgart, Stuttgart, Germany.
Tobias SiebertStuttgart Center for Simulation Science, University of Stuttgart, Stuttgart, Germany.
Geoffrey G HandsfieldAuckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
Oliver RöhrleInstitute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: In this paper, we introduce a novel method for determining 3D deformations of the human tibialis anterior (TA) muscle during dynamic movements using 3D ultrasound. Materials and Methods: An existing automated 3D ultrasound system is used for data acquisition, which consists of three moveable axes, along which the probe can move. While the subjects perform continuous plantar- and dorsiflexion movements in two different controlled velocities, the ultrasound probe sweeps cyclically from the ankle to the knee along the anterior shin. The ankle joint angle can be determined using reflective motion capture markers. Since we considered the movement direction of the foot, i.e., active or passive TA, four conditions occur: slow active, slow passive, fast active, fast passive. By employing an algorithm which defines ankle joint angle intervals, i.e., intervals of range of motion (ROM), 3D images of the volumes during movement can be reconstructed. Results: We found constant muscle volumes between different muscle lengths, i.e., ROM intervals. The results show an increase in mean cross-sectional area (CSA) for TA muscle shortening. Furthermore, a shift in maximum CSA towards the proximal side of the muscle could be observed for muscle shortening. We found significantly different maximum CSA values between the fast active and all other conditions, which might be caused by higher muscle activation due to the faster velocity. Conclusion: In summary, we present a method for determining muscle volume deformation during dynamic contraction using ultrasound, which will enable future empirical studies and 3D computational models of skeletal muscles.

Indexed as

3D ultrasoundcontractiondynamic movementimage processingmuscle deformation

Identifiers

PMID38903187
PMCPMC11188672

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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.