Evidence map›Paper›PMID 29670002›Full record

ArticleInternational journal of environmental research and public health2018

Assessment of Whole Body and Local Muscle Fatigue Using Electromyography and a Perceived Exertion Scale for Squat Lifting.

Imran Ahmad, Jung-Yong Kim

Registry-linked trialAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05813613 (Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training In Healthy And Post COVID19 Subjects), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

NCT05813613 completednot on this mapstarted 2023, after this paper: background citation

Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training In Healthy And Post COVID19 Subjects

TypeobservationalSponsorBeirut Arab UniversityRan2023 to 2023Enrolled90ConditionsFatigueArmsSquatting with the aid of Kynapsis Virtual Training apparatus.
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. [Cluster-guided adaptive Transformer for muscle fatigue prediction].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
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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

2 authors.

Imran AhmadDepartment of Industrial Management Engineering, Hanyang University, Ansan 15588, Korea. imran86@hanyang.ac.kr.
Jung-Yong KimDepartment of Industrial Management Engineering, Hanyang University, Ansan 15588, Korea. jungkim@hanyang.ac.kr.ORCID 0000-0003-4186-5978

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research study aims at addressing the paradigm of whole body fatigue and local muscle fatigue detection for squat lifting. For this purpose, a comparison was made between perceived exertion with the heart rate and normalized mean power frequency (NMPF) of eight major muscles. The sample consisted of 25 healthy males (age: 30 ± 2.2 years). Borg’s CR-10 scale was used for perceived exertion for two segments of the body (lower and upper) and the whole body. The lower extremity of the body was observed to be dominant compared to the upper and whole body in perceived response. First mode of principal component analysis (PCA) was obtained through the covariance matrix for the eight muscles for 25 subjects for NMPF of eight muscles. The diagonal entries in the covariance matrix were observed for each muscle. The muscle with the highest absolute magnitude was observed across all the 25 subjects. The medial deltoid and the rectus femoris muscles were observed to have the highest frequency for each PCA across 25 subjects. The rectus femoris, having the highest counts in all subjects, validated that the lower extremity dominates the sense of whole body fatigue during squat lifting. The findings revealed that it is significant to take into account the relation between perceived and measured effort that can help prevent musculoskeletal disorders in repetitive occupational tasks.

Indexed as

LiftingAdultElectromyographyHeart RateHumansMaleMuscle FatigueMuscle, SkeletalPerceptionPhysical ExertionPostureassessmentBorg scaleelectromyographymusclemusculoskeletal disordersprincipal component analysissquatswhole body fatigue

Identifiers

PMID29670002
PMCPMC5923826

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Registered trials

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.