Evidence map›Paper›PMID 39744591›Full record

ArticleFrontiers in bioengineering and biotechnology2024

Robust kinetics estimation from kinematics via direct collocation.

Kuan Wang, Linlin Zhang, Leichao Liang, Jiang Shao, Xinpeng Chen, Huihao Wang

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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 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Kuan WangCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Linlin ZhangCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Leichao LiangCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Jiang ShaoYangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China.
Xinpeng ChenYangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China.
Huihao WangShi's Center of Orthopedics and Traumatology (Institute of Traumatology, Shuguang Hospital), Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Accurate joint moment analysis is essential in biomechanics, and the integration of direct collocation with markerless motion capture offers a promising approach for its estimation. However, markerless motion capture can introduce varying degrees of error in tracking trajectories. This study aims to evaluate the effectiveness of the direct collocation method in estimating kinetics when joint trajectory data are impacted by noise. Methods: We focused on walking and squatting movements as our target activities. To assess the method's robustness, we created five groups with differing noise levels-noise-free, mild noise, noisy group1, noisy group2, and a Gaussian noise group-in the joint center trajectories. Our approach involved combining joint center tracking with biological terms within the direct collocation scheme to address noise-related challenges. We calculated kinematics, joint moments, and ground reaction forces for comparison across the different noise groups. Results: For the walking task, the mean absolute errors (MAEs) for the knee flexion moments were 0.103, 0.113, 0.127, 0.129, and 0.116 Nm/kg across the respective noise levels. The corresponding MAEs of the ankle flexion moment were 0.130, 0.133, 0.145, 0.131, and 0.138 Nm/kg. The hip flexion moment had MAEs of 0.182, 0.204, 0.242, 0.246, and 0.249 Nm/kg in the respective groups. In squatting, the MAEs of ankle flexion moments were 0.207, 0.219, 0.217, 0.253, and 0.227 Nm/kg in the noise-free, mild noise, noisy group1, noisy group2, and the Gaussian noise group, respectively. The MAEs of the knee flexion moments were 0.177, 0.196, 0.198, 0.197, and 0.221 Nm/kg, whereas the mean MAEs of the hip flexion moments were 0.125, 0.135, 0.141, 0.161, and 0.178 Nm/kg in the respective groups. Conclusion: The results highlight that the direct collocation method incorporating both tracking and biological terms in the cost function could robustly estimate joint moments during walking and squatting across various noise levels. Currently, this method is better suited to reflect general activity dynamics than subject-specific dynamics in clinical practice. Future research should focus on refining cost functions to achieve an optimal balance between robustness and accuracy.

Indexed as

direct collocationground reaction forcekinematicskineticssimulation

Identifiers

PMID39744591
PMCPMC11688375

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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.