Evidence map›Paper›PMID 35463289›Full record

ArticleComputational intelligence and neuroscience2022

Technical Diagnosis on Elite Female Discus Athletes Based on Grey Relational Analysis.

Dong Chen, Xuejun Ma, Jiawei Dong

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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
  2. 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

3 authors.

Dong ChenChina Athletics College, Beijing Sport University, Beijing 100085, China.ORCID https://orcid.org/0000-0001-7338-7937
Xuejun MaChina Athletics College, Beijing Sport University, Beijing 100085, China.ORCID https://orcid.org/0000-0001-8069-293X
Jiawei DongChina Athletics College, Beijing Sport University, Beijing 100085, China.ORCID https://orcid.org/0000-0002-5797-0169

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The personalized training of elite athletes is the key to the breakthrough of Chinese track and field events in the Tokyo Olympic Games. The brilliance of Chinese women's throwing benefits from the closed-loop personalized training system. Training starts from the construction of accurate personalized technology and physical fitness model. This paper introduces the concept of champion model and puts forward a targeted technical training system based on the differentiation research of champion model. This paper mainly studies and analyzes some important technical parameters and achievements of elite female discus athletes aged 2018∼2021 by using the methods of Pearson, partial correlation and grey correlation analysis. We select from several technical parameters with significant differences, choose from several technical parameters that have significant difference, and calculate the correlation parameters and results. The results show that the influence degree of these technical parameters is as follows: torso angle of right foot touching the ground, discus release angle, discus release speed, shoulder and arm passing angle of left foot off the ground, discus moving distance of double support, center of mass moving distance of double support, and time of the second single support stage. This is different from our view that the hand speed is the most important, so the training of elite athletes should be more refined and specialized to promote the improvement of their performance. Through the application of technical diagnosis model in Chen Yang in a period of time, Chen Yang got her best result (65.14 m) in Chongqing Athletics Championship, which verified the success of the technical diagnosis model and application in this study.

Indexed as

Track and FieldAthletesBiomechanical PhenomenaFemaleFootHumans

Identifiers

PMID35463289
PMCPMC9033319

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.