Evidence map›Paper›PMID 39738330›Full record

ArticleScientific reports2024

The assessment of sports performance by grip pressure using flexible piezoresistive pressure sensors in seven sports events.

Kebao Zhang, Beilei Guo, Mingchuan Yang, Yi Jia, Kehu Zhang, Liu Wang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Evaluating tennis player performance based on different types of grip strength.BMC sports science, medicine & rehabilitation · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

6 authors.

Kebao ZhangSchool of Sport and Physical Education, North University of China, Taiyuan, 030051, China.
Beilei GuoNursing Science, Jin Cheng People's Hospital, Shanxi, 048000, China.
Mingchuan YangScience and Technology on Electronic Test and Measurement Laboratory, North University of China, Taiyuan, 030051, China.
Yi JiaSchool of Sport and Physical Education, North University of China, Taiyuan, 030051, China.
Kehu ZhangPublishing Center, North University of China, Taiyuan, 030051, China. kehuzhang@qq.com.
Liu WangSchool of Recreation and Community Sport, Capital University of Physical Education and Sports, Beijing, 100191, China. wangliu@cupes.edu.cn.

Funding

National Social Science Foundation Major Project 23&ZD196
6 · The paper itself

Abstract

Flexible micro-sensors have significant application potential in the field of sports performance evaluation. The aim of this study is to assess sports performance by grip pressure using a MMSS sensor (MXene as the sensitive material and melamine sponge as the substrate, a type of flexible piezoresistive pressure sensor). The grip pressures of expert and amateur players are evaluated in single skills events (golf, billiards, basketball, javelin and shot put) and in skills conversion (badminton and tennis). Indicators (time nodes, intervals, peaks, etc.) related to grip pressure on the handle are collected, analyzed, and identified by artificial intelligence. Finally, the K-Nearest Neighbor (KNN) of artificial intelligence algorithms is employed to identify differences for 400 strokes of tennis players in interval training session. Expert tennis athlete exhibits a higher level of precision, concentration and stability for exert and release of grip force (KNN accuracy of train 95.0%) than amateur (KNN: 84.6%) during single movement, technical conversion, and interval training condition. This research offers a new perspective for evaluating sports performance in hand-held equipment events and presents a feasible direction for facing challenges of flexible wearable technology in practice.

Indexed as

Athletic PerformanceHand StrengthAdultAlgorithmsArtificial IntelligenceAthletesFemaleHumansMalePressureSportsTennisWearable Electronic DevicesYoung AdultArtificial intelligenceAssessment of sports performanceGrip pressure releaseKinematic chainPiezoresistive sensorsReal scenario

Identifiers

PMID39738330
PMCPMC11686128

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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.