Evidence map›Paper›PMID 41388055›Full record

ArticleScientific reports2025

Evaluating the swimming technique analysis: a multi-criteria decision approach using hesitant bipolar fuzzy with a GRA approach.

Qing Li, Jianxia Yin

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
–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

1 citing paper in PubMed.

  1. 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

2 authors.

Qing LiSwimming Teaching and Research Office, Xi'an Physical Education University, Xi'an, 710068, Shaanxi, China.
Jianxia YinSwimming Teaching and Research Office, Xi'an Physical Education University, Xi'an, 710068, Shaanxi, China. yjx949@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern technology has played a significant role in improving the analysis and training of swimming, providing more accurate results. Also, finding the best swimming technique is still complicated because there are conflicting standards and uncertainty among experts. This study builds a decision framework using hesitant bipolar fuzzy sets (HBFS) and the grey relational analysis (GRA) method to deal with expert hesitations and bipolar opinions. Freestyle, breaststroke, butterfly, backstroke, and sidestroke are tested against what they accomplish in terms of speed, energy they use, how smooth they look during execution, and the efficiency of their breathing. Based on the HBFS-GRA approach, the experts considered the butterfly stroke the most suitable technique. The new process increases objectivity and makes decisions in sports science less vague. This study also recognizes some challenges, including using experts' subjective opinions, missing data, and the need to regularly update the analysis due to the quick development of sports technologies. In the future, the system could be enhanced by including data from wearable devices and discussion with artificial intelligence, as well as by adapting it to cover different sports disciplines. This research promotes using data and well-structured models to assess athlete performance.

Indexed as

Athletic PerformanceDecision Support TechniquesFuzzy LogicSwimmingAlgorithmsDecision MakingHumansDecision support systemGRA methodHesitant bipolar fuzzySwimming technique analysisTechnology evaluation

Identifiers

PMID41388055
PMCPMC12756220

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.