A new method called MiKneeSoTA to minimize knee soft-tissue artifacts in kinematic analysis

The use of marker-based optical motion capture to estimate joint kinematics during gait is currently limited by errors associated with soft-tissue-induced motion artefacts (STIMA) and ambiguity in landmark palpation. This study therefore presents a novel protocol aiming to Minimize Knee Soft-Tissue Artefacts (MiKneeSoTA) and their effect on kinematic estimates. Relying on an augmented marker set and a new inverse kinematics approach, our method leverages frame-by-frame optimization to adjust best-fit cylinders that have been automatically generated based on the relative position of lower limb markers during an initial static trial. Tibiofemoral rotations and translations are then calculated along the anatomical joint axes based on the relative 3D motion of these cylinders. When compared against the conventional Helen-Hayes approach, in vivo assessment of fifteen healthy subjects revealed the MiKneeSoTA approach led to kinematic profiles with significantly lower standard deviations in joint rotations across trials, and even visibly reduced the presence of high frequency fluctuations presumably associated with e.g. soft-tissue vibration. In addition to agreeing with previously published bone pin and fluoroscopy datasets, our results illustrate MiKneeSoTA's ability to abate the effect of STIMA induced by lateral knee ligaments. Our findings indicate that MiKneeSoTA is in fact a promising approach to mitigate knee joint STIMA and thus enable the previously unattainable accurate estimation of translational knee joint motion with an optoelectronic system.

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Publication Details

Journal
Scientific Reports
Published
2024-09-05
DOI
https://doi.org/10.1038/s41598-024-71409-z
Citations
5
Primary Topic
Lower Extremity Biomechanics and Pathologies
Type
article
Field-Weighted Citation Impact
0.92
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article

A new method called MiKneeSoTA to minimize knee soft-tissue artifacts in kinematic analysis

Adrian Sauer, Michael Utz, Eike Jakubowitz, Ann‐Kathrin Einfeldt et al.
5 citations
Scientific Reports
Lower Extremity Biomechanics and Pathologies
0.92
article

A new method called MiKneeSoTA to minimize knee soft-tissue artifacts in kinematic analysis

Adrian Sauer, Michael Utz, Eike Jakubowitz, Ann‐Kathrin Einfeldt, Leon Budde, Ariana Ortigas-Vásquez
article en
5 citations

Abstract

The use of marker-based optical motion capture to estimate joint kinematics during gait is currently limited by errors associated with soft-tissue-induced motion artefacts (STIMA) and ambiguity in landmark palpation. This study therefore presents a novel protocol aiming to Minimize Knee Soft-Tissue Artefacts (MiKneeSoTA) and their effect on kinematic estimates. Relying on an augmented marker set and a new inverse kinematics approach, our method leverages frame-by-frame optimization to adjust best-fit cylinders that have been automatically generated based on the relative position of lower limb markers during an initial static trial. Tibiofemoral rotations and translations are then calculated along the anatomical joint axes based on the relative 3D motion of these cylinders. When compared against the conventional Helen-Hayes approach, in vivo assessment of fifteen healthy subjects revealed the MiKneeSoTA approach led to kinematic profiles with significantly lower standard deviations in joint rotations across trials, and even visibly reduced the presence of high frequency fluctuations presumably associated with e.g. soft-tissue vibration. In addition to agreeing with previously published bone pin and fluoroscopy datasets, our results illustrate MiKneeSoTA's ability to abate the effect of STIMA induced by lateral knee ligaments. Our findings indicate that MiKneeSoTA is in fact a promising approach to mitigate knee joint STIMA and thus enable the previously unattainable accurate estimation of translational knee joint motion with an optoelectronic system.

Scientific ReportsVol. 14(1)
Leibniz University Hannover (DE), Medizinische Hochschule Hannover (DE), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 28%
Lower Extremity Biomechanics and Pathologies
0.92
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