Evidence map›Paper›PMID 41270004›Full record

ArticlePloS one2025

Joint angle trajectories are Robust to segment length estimation methods in human reaching.

Rachel I Taitano, Valeriya Gritsenko

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Rachel I TaitanoDepartment of Neuroscience, School of Medicine, West Virginia University, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, United States of America.ORCID https://orcid.org/0000-0002-9786-4985
Valeriya GritsenkoDepartment of Neuroscience, School of Medicine, West Virginia University, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, United States of America.ORCID https://orcid.org/0000-0002-6408-9433

Funding

West Virginia University Stroke COBREP20GM109098 · NIGMS · WEST VIRGINIA UNIVERSITY · PI HRUSKA, MARTIN · 2014 to 2024
$24.5M
Stroke and Alzheimers Disease Related DementiasT32AG052375 · NIA · WEST VIRGINIA UNIVERSITY · PI Paul D Chantler, BERNARD G. SCHREURS · 2017 to 2026
$3.5M
COBRE Transitional Center in NeuroscienceP30GM103503 · NIGMS · WEST VIRGINIA UNIVERSITY · PI SPIROU, GEORGE A · 2012 to 2014
$3.2M
NIA NIH HHS T32 AG052375NIGMS NIH HHS P20 GM109098NIGMS NIH HHS P30 GM103503
6 · The paper itself

Abstract

backgroundQuantitative movement analysis is increasingly used to assess motor deficits, but joint angle calculations depend on assumptions about limb segment lengths. These lengths are often estimated from average anthropometric proportions rather than measured directly. The extent to which such assumptions influence joint angle accuracy and variability remains unclear.

methodsIn prior studies, we recorded reaching movements in nine healthy adults using active-marker motion capture system. In this study, we computed arm joint angles with a dynamic model scaled using either measured segment lengths (Individual method) or proportions based on body height (Average method). Each participant served as their own control across two modeling conditions. We compared segment proportions and the variability in joint angle trajectories arising from segment length assumptions (between-participant variability) with within-participant variability across repeated movements.

resultsSegment length proportions remained unchanged despite increases in population height. Joint angle trajectories derived from the two scaling methods were very similar. Segment length assumptions had only minor effects on joint angle amplitudes, primarily due to kinematic redundancy, and these effects were substantially smaller than the within-participant variability observed across repeated movements in most individuals. Importantly, while segment length estimates shifted absolute joint angle amplitudes, they did not alter the shape of angular trajectories. CONCLUSIONS/SIGNIFICANCE: Morphological variability in segment lengths contributes less to joint angle variability than the variability expressed by individuals across repeated movements. This indicates that movement variability inherent in movement execution outweighs that introduced by morphological differences. These findings suggest that motion capture-based assessments of reaching quality remain accurate even when segment lengths are inferred from height, supporting their practical use in remote or telehealth clinical assessments where direct anthropometry is not feasible.

Indexed as

ArmJointsAdultBiomechanical PhenomenaFemaleHumansMaleMovementRange of Motion, ArticularYoung Adult

Identifiers

PMID41270004
PMCPMC12637938

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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.