Evidence map›Paper›PMID 41323870›Full record

ArticleFrontiers in sports and active living2025

Quantifying gait compensation in knee osteoarthritis using smartphone-based motion capture (OpenCap).

Jia-Jing Xu, Yi Xu, Peng-Fei Shi, An Shao, Jin-Tao Pan, Xi-Ping Ren, Shi-Jia Wang, Yong-Wei Zhou, Lian-Ping Jiang, Qi-Ning Yang

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Jia-Jing Xu *Jinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.
Yi Xu *Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands.
Peng-Fei ShiJinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.
An ShaoJinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.
Jin-Tao PanCollege of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, China.
Xi-Ping RenCollege of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, China.
Shi-Jia WangJinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.
Yong-Wei ZhouJinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.
Lian-Ping Jiang *Jinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.
Qi-Ning Yang *Jinhua Municipal Central Hospital, Zhejiang University, Jinhua City, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Knee osteoarthritis (KOA) is one of the most prevalent degenerative joint diseases, and its pathological features often lead to abnormal gait patterns and limited joint mobility. These changes induce various degrees of lower-limb compensatory mechanisms that significantly affect patients' quality of life and increase their risk of falls. An accurate and objective assessment of these gait changes and compensatory strategies is critical for clinical diagnosis, monitoring of disease progression, and the formulation of rehabilitation strategies. Objective: This study aims to investigate the compensatory mechanisms of lower limb kinematics in KOA patients during walking using a markerless motion capture system-OpenCap-and toevaluate its feasibility and accuracy in a clinical environment. Methods: A total of 33 KOA patients and 78 healthy control participants were enrolled. Two smartphones were used to record videos of participants walking along a flat path, and OpenCap was employed to calculate spatiotemporal gait parameters and 3D joint kinematics. Data were statistically analyzed to determine differences in gait features between KOA patients and controls. Results: KOA patients had significantly reduced walking speed and stride length, and exhibited increased step width, reduced knee flexion-extension range, and greater pelvic tilt and hip internal rotation during certain phases of the gait cycle. These findings reflect biomechanical compensation strategies related to joint pain, instability, or restricted mobility. OpenCap provided reliable and accurate motion data and demonstrated strong potential for hospital-based gait assessments due to its low cost and ease of setup. Significance: This study demonstrated that OpenCap effectively captures KOA-related gait abnormalities and compensatory joint movements. Its low cost and ease of use support its application in hospital settings for dynamic evaluation and rehabilitation planning.

Indexed as

biomechanical gait analysisknee osteoarthritisOpenCaprange of motionsmartphone-based motion capture system

Identifiers

PMID41323870
PMCPMC12657453

What Socratic holds

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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.