Physiology-based dynamic muscle fatigue model for upper limbs during construction tasks

Houtan Jebelli, Joon Oh Seo, Sungjoo Hwang, Sang Hyun Lee

Research output: Contribution to journalArticle

Abstract

Due to physically demanding construction tasks, workers frequently suffer from significant levels of muscle fatigue that can cause diverse detrimental effects on safety, health, and productivity. In this regard, evaluating the level of muscle fatigue prior to work is essential to take proper preventive actions before severe fatigue takes place. Although previous research efforts have quantified muscle fatigue using surveys, instruments, and mathematical models, most of them do not take into account irregularly varying muscle activation and fatigue recovery during a task. They are thus limited, especially for construction tasks that have varying forces and intermittent idling/resting periods. This study thus proposes a physiology-based modeling approach to computationally model and empirically validate dynamic muscle fatigue generation and recovery for construction workers through laboratory testing. Specifically, a muscle fatigue estimation model for upper limbs based on System Dynamics, which is a differential equation-based continuous simulation, is developed based on fundamental physiological mechanisms of the accumulation and clearance of intramuscular metabolites during muscle exertion and their effects on muscle contractile processes. Then the model is refined and validated through laboratory experiments. The results demonstrated the immense potential for the developed elbow and shoulder models to evaluate workers' muscle fatigue in upper limbs under varying workloads. The contribution of this study is to provide an analytic tool for understanding the physiological mechanisms of muscle fatigue and estimating workers' muscle fatigue levels during construction tasks, which can help to design appropriate interventions prior to work, thereby reducing undesirable results from muscle fatigue.

Original languageEnglish (US)
Article number102984
JournalInternational Journal of Industrial Ergonomics
Volume78
DOIs
StatePublished - Jul 2020

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Public Health, Environmental and Occupational Health

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