Evidence map›Paper›PMID 40982182›Full record

ArticleAnnals of biomedical engineering2025

Dual-Camera Markerless Motion Capture System for Precise Lower-Limb Kinematic Analysis in Osteoarthritis.

Bo Hu, Junqing Wang, Wei Xu, Tengfei Li, Yong Nie, Kang Li

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Article in Annals of biomedical engineering, 2025. 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

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Bo Hu *Department of Orthopedic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan Province, China.
Junqing Wang *Department of Orthopedic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan Province, China.
Wei Xu *Department of Orthopedic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan Province, China.
Tengfei LiDepartment of Orthopedic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan Province, China.
Yong NieDepartment of Orthopedic Surgery and Orthopedic Research Institute, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan Province, China. nieyong1983@wchscu.cn.ORCID http://orcid.org/0000-0002-6132-379X
Kang LiDepartment of Orthopedic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan Province, China. likang@wchscu.cn.ORCID http://orcid.org/0000-0002-8136-9816

Funding

1•3•5 project for disciplines of excellence ZYYC210041•3•5 project for disciplines of excellence-Clinical Research Fund 2023HXFH0241•3•5 projects for Artificial Intelligence West China Hospital ZYAI24038Sichuan Provincial International Science and Technology Innovation Cooperation 2025YFHZ0110the National Key Research and Development Program 2023YFB4606700
6 · The paper itself

Abstract

purposeThis study aimed to develop a dual-camera markerless system based on data from patients with osteoarthritis (OA) and validate its agreement with a marker-based motion capture system for measuring lower-limb kinematics.

methodsA total of 152 OA patients were divided into a training set (n = 120) and a test set (n = 32). Kinematic data during gait were collected simultaneously via both markerless and marker-based systems. The dual-camera markerless system consists of a 2D pose extractor based on a neural network and 3D triangulation, and the kinematic differences between the two systems were evaluated via the root mean square distance (RMSD) and root mean square error (RMSE) and intraclass correlation coefficient (ICC).

resultsThe markerless system demonstrated great performance, achieving a grand mean RMSD of 11.0 mm and an ICC of 0.95 for keypoints. Joint angle analysis revealed a mean RMSE of 4.25°, with ICC values for joint angle waveforms reaching 0.90 in the sagittal plane, 0.48 in the frontal plane, and 0.24 in the transverse plane compared with the marker-based system.

conclusionThese results indicate that the dual-camera markerless system provides accurate lower-limb kinematic measurements for patient populations while offering significant advantages in terms of cost-effectiveness, installation simplicity, and reduced operational expertise requirements, facilitating efficient biomechanical assessment in clinical use.

Indexed as

GaitLower ExtremityOsteoarthritisAgedBiomechanical PhenomenaFemaleHumansMaleMiddle AgedMotion CaptureArtificial intelligenceBiomechanicsGait analysisMarkerless motion captureTriangulation

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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.