Evidence map›Paper›PMID 41400764›Full record

ArticleMedical & biological engineering & computing2026

A mobile tool for static standing posture assessment using accurate 3D body reconstruction.

Qingguang Chen, Yingying Pan, Xinghao Zhang, Jiajin Liu, Liang Song, Yufang Xu, Hang Lu, Wenhan Luo

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Article in Medical & biological engineering & computing, 2026. 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

8 authors.

Qingguang ChenSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China. optichen@hdu.edu.cn.
Yingying PanSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China.
Xinghao ZhangSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China.
Jiajin LiuSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China.
Liang SongSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China.
Yufang XuDepartment of Physical Education and Military Training, China Jiliang University, Hangzhou, 310018, China.
Hang LuSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China.
Wenhan LuoSchool of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China.

Funding

Natural Science Foundation of Zhejiang Province LTGY23F030001
6 · The paper itself

Abstract

Accurate posture assessment is essential for diagnosing and managing health issues related to postural disorders. Existing mobile applications rely on 2D imaging and analyzing reflective markers placed on anatomical landmarks of the human body without comprehensive view of body's posture. A mobile tool of 3D body reconstruction-based posture assessment is proposed in this paper. A smartphone is used to capture video circling around a static standing person in an approximate A-pose. Some specific multi-view body images using body orientation estimation are extracted from video. Then OpenPose and U2Net are employed to extract 2D joints and contours of each image. Camera poses are estimated using feature matching, and 3D joints are reconstructed from 2D joints and camera parameters. Multi-view projection contour consistency is used to iteratively optimize SMPL parameters for accurate 3D body reconstruction. From reconstructed 3D SMPL body, the required parameters for posture assessment including key 3D body points, joint angles, and spatial measurements, etc. can be easily obtained and calculated. Finally, assessment results are compared with artificial intelligence posture evaluation and correction system (APECS), and reliability is evaluated using Cohen's d and the Intraclass Correlation Coefficient (ICC). The proposed 3D body-based method achieved over 90% accuracy in identifying common postural abnormalities, such as uneven shoulders and forward head posture. The posture assessment results were in close agreement with existing method. 3D body reconstruction is demonstrated to be an effective method for posture assessment. Smartphone video-based posture assessment provides a user-friendly, visualized, abnormal posture screening tool.

Indexed as

Imaging, Three-DimensionalMobile ApplicationsPostureStanding PositionAdultAlgorithmsFemaleHumansImage Processing, Computer-AssistedMaleReproducibility of ResultsSmartphoneVideo Recording3D body reconstructionMulti-view imagesPosture assessmentSmartphone application

Identifiers

What OpenQuestion holds

Textmetadata
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.