Evidence map›Paper›PMID 35178224›Full record

ArticleJournal of healthcare engineering2022

Biomechanical Process of Skeletal Muscle under Training Condition Based on 3D Visualization Technology.

Chen Chen

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 55% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Special Issue "Biomechanical Analysis in Physical Activity and Sports".Journal of functional morphology and kinesiology · 2025
    Article
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

1 author at 1 institution in 1 country.

Chen ChenXi'an International Studies University, Xi'an, Shaanxi 710128, China.ORCID 0000-0003-3947-1136
Xi'an International Studies University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the development and popularization of 3D technology, human behavior recognition has gradually developed from plane feature recognition to elevation feature recognition. In the process of collecting motion characteristics, the research on skeletal muscle will lead to a series of data in time series, which is the basis of sports biomechanics research and sports training. Some important semantic information such as centerline and joint center can be obtained by further data processing. The results of the study showed that the three-dimensional coordinate positions of the femur and pelvic attachment points of the muscles surrounding the hip joint from the pelvis were measured and positioned. A 3D model is built to simulate the human skeletal model subjected to speeds of 3 and 7 m/s, and different motion velocities can exhibit different motions. The research in this study shows that using 3D technology and comprehensively utilizing the expertise of biomechanical analysis and graphical modeling to study the mechanical properties of bone joints and soft tissues provide new ways and methods.

Indexed as

Hip JointImaging, Three-DimensionalBiomechanical PhenomenaHumansMuscle, SkeletalTechnology

Identifiers

PMID35178224
PMCPMC8846985
OpenAlexW4210844523

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.