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Modelling endurance and resumption times for repetitive one-hand pushing
KTH, School of Technology and Health (STH), Health Systems Engineering.ORCID iD: 0000-0002-7565-854X
Ryerson Univ, Dept Phys, Toronto, ON, Canada.;RIKEN, Interdisciplinary Theoret & Math Sci iTHES, iTHEMS, Res Grp, Wako, Saitama, Japan..
Ryerson Univ, Dept Mech & Ind Engn, Human Factors Engn Lab, Toronto, ON, Canada..
2018 (English)In: Ergonomics, ISSN 0014-0139, E-ISSN 1366-5847, Vol. 61, no 7, p. 891-901Article in journal (Refereed) Published
Abstract [en]

This study's objective was to develop models of endurance time (ET), as a function of load level (LL), and of resumption time (RT) after loading as a function of both LL and loading time (LT) for repeated loadings. Ten male participants with experience in construction work each performed 15 different one-handed repetaed pushing tasks at shoulder height with varied exerted force and duration. These data were used to create regression models predicting ET and RT. It is concluded that power law relationships are most appropriate to use when modelling ET and RT. While the data the equations are based on are limited regarding number of participants, gender, postures, magnitude and type of exerted force, the paper suggests how this kind of modelling can be used in job design and in further research.Practitioner Summary: Adequate muscular recovery during work-shifts is important to create sustainable jobs. This paper describes mathematical modelling and presents models for endurance times and resumption times (an aspect of recovery need), based on data from an empirical study. The models can be used to help manage fatigue levels in job design.

Place, publisher, year, edition, pages
TAYLOR & FRANCIS LTD , 2018. Vol. 61, no 7, p. 891-901
Keyword [en]
Modelling, endurance, recovery, work-rest, repetitive load
National Category
Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-227792DOI: 10.1080/00140139.2018.1427282ISI: 000430482000002PubMedID: 29320970Scopus ID: 2-s2.0-85042136805OAI: oai:DiVA.org:kth-227792DiVA, id: diva2:1205311
Funder
AFA Insurance, 0800030SBUF - Sveriges Byggindustriers Utvecklingsfond, 12008Forte, Swedish Research Council for Health, Working Life and Welfare, 2008-1810
Note

QC 20180514

Available from: 2018-05-14 Created: 2018-05-14 Last updated: 2018-05-14Bibliographically approved

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