Evidence map›Paper›PMID 33114105›Full record

ArticleSensors (Basel, Switzerland)2020

Feasibility of Smartphone-Based Badminton Footwork Performance Assessment System.

Ya-Lan Chiu, Chia-Liang Tsai, Wen-Hsu Sung, Yi-Ju Tsai

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

4 authors.

Ya-Lan ChiuDepartment of Physical Therapy, National Cheng Kung University, Tainan 701, Taiwan.
Chia-Liang TsaiInstitution of Physical Education, Health and Leisure Studies, National Cheng Kung University, Tainan 701, Taiwan.ORCID 0000-0001-6173-2879
Wen-Hsu SungDepartment of Physical Therapy and Assistive Technology, National Yang-Ming University, Taipei 112, Taiwan.ORCID 0000-0002-0129-208X
Yi-Ju TsaiDepartment of Physical Therapy, National Cheng Kung University, Tainan 701, Taiwan.ORCID 0000-0003-4082-2634

Funding

Ministry of Science and Technology, Taiwan MOST 109-2627-H-006-004Ministry of Science and Technology, Taiwan MOST 109-2811-H-006-503
6 · The paper itself

Abstract

Footwork is the most fundamental skill in badminton, involving the ability of acceleration or deceleration and changing directions on the court, which is related to accurate shots and better game performance. The footwork performance in-field is commonly assessed using the total finished time, but does not provide any information in each direction. With the higher usage of the smartphones, utilizing their built-in inertial sensors to assess footwork performance in-field might be possible by providing information about body acceleration in each direction. Therefore, the purpose of this study was to evaluate the feasibility of a smartphone-based measurement system on badminton six-point footwork. The body acceleration during the six-point footwork was recorded using a smartphone fixed at the belly button and a self-developed application in thirty badminton players. The mean and maximum of the acceleration resultant for each direction of the footwork were calculated. The participants were classified into either the faster or slower group based on the finished duration of footwork. Badminton players who finished the footwork faster demonstrated a greater mean and maximum acceleration compared to those who finished slower in most directions except for the frontcourt directions. The current study found that using a smartphone's built-in accelerometer to evaluate badminton footwork is feasible.

Indexed as

accelerationbadmintonfootworksmartphone

Identifiers

PMID33114105
PMCPMC7660291

What OpenQuestion holds

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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.