Evidence map›Paper›PMID 39369227›Full record

SynthesisJournal of neuroengineering and rehabilitation2024

Multibody dynamics-based musculoskeletal modeling for gait analysis: a systematic review.

Muhammad Abdullah, Abdul Aziz Hulleck, Rateb Katmah, Kinda Khalaf, Marwan El-Rich

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of neuroengineering and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Trial
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  3. [Personalized lower-limb gait assessment method based on musculoskeletal modeling and machine learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
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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

5 authors.

Muhammad AbdullahDepartment of Mechanical and Nuclear Engineering, Khalifa University, Abu Dhabi, UAE.
Abdul Aziz HulleckDepartment of Mechanical and Nuclear Engineering, Khalifa University, Abu Dhabi, UAE.
Rateb KatmahDepartment of Biomedical and Biotechnology Engineering, Khalifa University, Abu Dhabi, UAE.
Kinda KhalafDepartment of Biomedical and Biotechnology Engineering, Khalifa University, Abu Dhabi, UAE.
Marwan El-RichDepartment of Mechanical and Nuclear Engineering, Khalifa University, Abu Dhabi, UAE. marwan.elrich@ku.ac.ae.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Beyond qualitative assessment, gait analysis involves the quantitative evaluation of various parameters such as joint kinematics, spatiotemporal metrics, external forces, and muscle activation patterns and forces. Utilizing multibody dynamics-based musculoskeletal (MSK) modeling provides a time and cost-effective non-invasive tool for the prediction of internal joint and muscle forces. Recent advancements in the development of biofidelic MSK models have facilitated their integration into clinical decision-making processes, including quantitative diagnostics, functional assessment of prosthesis and implants, and devising data-driven gait rehabilitation protocols. Through an extensive search and meta-analysis of over 116 studies, this PRISMA-based systematic review provides a comprehensive overview of different existing multibody MSK modeling platforms, including generic templates, methods for personalization to individual subjects, and the solutions used to address statically indeterminate problems. Additionally, it summarizes post-processing techniques and the practical applications of MSK modeling tools. In the field of biomechanics, MSK modeling provides an indispensable tool for simulating and understanding human movement dynamics. However, limitations which remain elusive include the absence of MSK modeling templates based on female anatomy underscores the need for further advancements in this area.

Indexed as

Gait AnalysisBiomechanical PhenomenaGaitHumansModels, BiologicalMuscle, SkeletalAnyBody modeling systemGait analysisMotion captureMusculoskeletal modelingOpenSimPersonalization

Identifiers

PMID39369227
PMCPMC11452939

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.