Evidence map›Paper›PMID 41959795›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Smartphone video-based knee extension moments during chair rise relate to MRI measures of muscle function.

R Daniel Magruder, Mary Hall, Yael Vainberg, Jessica L Asay, Feliks Kogan, Jennifer L Hicks, Garry E Gold, Scott L Delp, Scott D Uhlrich, Valentina Mazzoli

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

R Daniel MagruderDepartment of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA.ORCID 0009-0004-8539-9678
Mary HallDepartment of Radiology, Stanford University, Stanford, CA, USA.
Yael VainbergDepartment of Radiology, Stanford University, Stanford, CA, USA.
Jessica L AsayDepartment of Radiology, Stanford University, Stanford, CA, USA.
Feliks KoganDepartment of Radiology, Stanford University, Stanford, CA, USA.
Jennifer L HicksDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Garry E GoldDepartment of Radiology, Stanford University, Stanford, CA, USA.
Scott L DelpDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Scott D UhlrichDepartment of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA.
Valentina MazzoliBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.

Funding

TR&D Project 3: OpenSim for PredictionP41EB027060 · NIBIB · STANFORD UNIVERSITY · PI SCOTT L DELP · 2020 to 2026
$9.7M
Technology DevelopmentP2CHD101913 · NICHD · STANFORD UNIVERSITY · PI KU, JOY P · 2020 to 2024
$4.1M
Resource CoreP50HD118632 · NICHD · STANFORD UNIVERSITY · PI SCOTT L DELP, Jennifer Lee Hicks · 2025 to 2026
$3.9M
Quantitative assessment of early structural and functional changes in aging skeletal muscleR00AG071735 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI MAZZOLI, VALENTINA · 2023 to 2025
$742k
Quantitative assessment of early structural and functional changes in aging skeletal muscleK99AG071735 · NIA · STANFORD UNIVERSITY · PI MAZZOLI, VALENTINA · 2021 to 2022
$206k
NIA NIH HHS K99 AG071735NIA NIH HHS R00 AG071735NIBIB NIH HHS P41 EB027060NICHD NIH HHS P2C HD101913NICHD NIH HHS P50 HD118632
6 · The paper itself

Abstract

Background: Preserving muscle function is essential for maintaining independence during aging, but muscle force-generating capacity is not commonly measured clinically due to a lack of accessible, sensitive tools. Magnetic resonance imaging (MRI) provides gold-standard measures of muscle volume and microstructure, which reflect force-generating capacity, while dynamometry quantifies peak joint moments during voluntary contraction. Both modalities are time-consuming and costly, so clinical and large-scale studies often rely on low-fidelity measures such as the time to complete the five times sit-to-stand test (5xSTS). OpenCap, a tool for quantifying musculoskeletal dynamics from smartphone videos, may provide an accessible and more informative approach to assessing muscle function. We evaluated whether OpenCap-derived knee extension moments during chair rise relate to MRI-based measures of quadriceps muscle volume and microstructure, using dynamometry as a comparator. Methods: Nineteen healthy adults of various ages (63.2% female, 57.8 ± 15.4 y, 30-78 y) underwent quadriceps MRI, dynamometry, and 5xSTS time with concurrent OpenCap data collection. Using MRI, we computed quadriceps volume and radial diffusivity (a measure related to fiber size). We standardized these features and summed to create a composite MRI score, reflecting muscle quantity and quality. We estimated peak knee extension moment using OpenCap during chair rise and via both isometric and isokinetic dynamometry. We compared OpenCap kinematics (torso angle) and dynamics (knee moment), 5xSTS time, and dynamometry to MRI measures of muscle function using linear regression; false discovery rate was controlled using the Benjamini-Hochberg procedure. Results: The OpenCap-derived knee extension moment was associated with quadriceps muscle volume (r=0.63, p=0.014) and radial diffusivity (r=0.61, p=0.016). Peak knee extension moments measured by both isometric and isokinetic dynamometry were correlated with muscle volume (r=0.66-0.75, p=0.002-0.009), but not with radial diffusivity (r=0.04-0.52, p=0.054-0.91). Both OpenCap and isokinetic dynamometry showed their strongest associations with the composite MRI score (r=0.77, p=0.002 and r=0.73, p=0.002, respectively). 5xSTS time and a kinematic feature (torso angle) were not associated with any MRI-derived measures (r=-0.16-0.35, p=0.22-0.97). Conclusions: Smartphone video-based joint moments associate with muscle size and microstructure, unlike time or kinematic features. OpenCap offers a scalable assessment of muscle force-generating capacity that can be conducted rapidly without specialized equipment, enabling higher-fidelity assessments of muscle function in the clinic and in large-scale studies where imaging and dynamometry are impractical.

Indexed as

agingbiomechanicsdynamometrymagnetic resonance imagingmuscle strengthsmartphone video

Identifiers

PMID41959795
PMCPMC13060989

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.