Evidence map›Paper›PMID 38087307›Full record

ArticleBiomedical engineering online2023

Comparison of plugin and redundant marker sets to analyze gait kinematics between different populations.

Run Ji, Wayne Yuk-Wai Lee, Xinyu Guan, Bin Yan, Lei Yang, Jiemeng Yang, Ling Wang, Chunjing Tao, Shengzheng Kuai, Yubo Fan

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 6 institutions in 2 countries.

Run JiSchool of Biological Science and Medical Engineering, School of Engineering Medicine, Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, 100191, China.
Wayne Yuk-Wai LeeDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong SAR, China.
Xinyu GuanSchool of Biological Science and Medical Engineering, School of Engineering Medicine, Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, 100191, China.
Bin YanDepartment of Spine Surgery, Shenzhen Second People's Hospital, Shenzhen, 518039, China.
Lei YangDepartment of Spine Surgery, Shenzhen Second People's Hospital, Shenzhen, 518039, China.
Jiemeng YangSchool of Biological Science and Medical Engineering, School of Engineering Medicine, Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, 100191, China.
Ling WangTianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, 300384, China.
Chunjing TaoSchool of Biological Science and Medical Engineering, School of Engineering Medicine, Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, 100191, China. chunjingtao@buaa.edu.cn.
Shengzheng KuaiDepartment of Spine Surgery, Shenzhen Second People's Hospital, Shenzhen, 518039, China. kkzh2008@126.com.
Yubo FanSchool of Biological Science and Medical Engineering, School of Engineering Medicine, Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, 100191, China. yubofan@buaa.edu.cn.
Beihang University · CNShenzhen Second People's Hospital · CNChinese University of Hong Kong · HKMinistry of Civil Affairs · CNNational Research Center for Rehabilitation Technical Aids · CNTianjin University of Technology · CN

Funding

National Key Research and Development Program of China No.2020YFC2005900National Natural Science Foundation of China No.12072
6 · The paper itself

Abstract

backgroundGait model consists of a marker set and a segment pose estimation algorithm. Plugin marker set and inverse kinematic algorithm (IK.) are prevalent in gait analysis, especially musculoskeletal motion analysis. Adding extra markers for the plugin marker set could increase the robustness to marker misplacement, motion artifacts, and even markers occlusion. However, how the different marker sets affect the gait analysis's kinematic output is unclear. Therefore, this study aims to investigate the effect of marker sets on the kinematic output during level walking in different populations.

resultsIn all three planes, there are significant differences (P < 0.05) between marker sets in some kinematic variables at the hip, knee, and ankle. In different populations, the kinematic variables that show significant differences varied. When comparing the kinematic differences between populations using the two marker sets separately, the range of motion (ROM) of hip flexion was only found to be a significant difference using the redundant marker set, while the peak internal rotation at the knee was only found a significant difference using plugin marker set. In addition, the redundant marker set shows less intra-subject variation than the plugin marker set.

conclusionThe findings in this study demonstrate the importance of marker set selection since it could change the result when comparing the kinematic differences between populations. Therefore, it is essential to increase the caution in explaining the result when using different marker sets. It is crucial to use the same marker set, and the redundant marker set might be a better choice for gait analysis.

Indexed as

GaitKneeBiomechanical PhenomenaHumansKnee JointRange of Motion, ArticularRotationWalkingGait modelInverse kinematic algorithmKinematicsMarker set

Identifiers

PMID38087307
PMCPMC10717987
OpenAlexW4389609920

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.