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A modified version of the three-compartment model to predict fatigue during submaximal tasks with complex force-time histories.
Sonne, Michael W; Potvin, Jim R.
Affiliation
  • Sonne MW; a Department of Kinesiology , McMaster University, Ivor Wynne Centre , Room 219A, 1280 Main Street West, Hamilton , Ontario , Canada L8S 4K1.
  • Potvin JR; a Department of Kinesiology , McMaster University, Ivor Wynne Centre , Room 219A, 1280 Main Street West, Hamilton , Ontario , Canada L8S 4K1.
Ergonomics ; 59(1): 85-98, 2016.
Article in En | MEDLINE | ID: mdl-26018327
The three-compartment model (3CM) was validated previously for prediction of endurance times by modifying its fatigue and recovery rates. However, endurance times do not typically represent work demands, and it is unknown if the current version of the 3CM is applicable for ergonomics analysis of all occupational tasks. The purpose of this study was to add biological fidelity to the 3CM, and validate the model against a series of submaximal force plateaus. The fatigue and recovery rates were modified to represent graded physiological motor unit characteristics (termed 3CM(GMU)). In nine experiments of submaximal efforts, the 3CM(GMU) produced a root-mean squared difference (RMSD) of 4.1 ± 0.5% MVC over experiments with an average strength loss (i.e., fatigue) of 31.0 ± 1.1% MVC. The 3CM(GMU) model performed poorly for endurance tasks. The 3CM(GMU) model is an improvement for evaluating submaximal force patterns consisting of intermittent muscle contractions of the hand and forearm. PRACTITIONER SUMMARY: We modified an existing fatigue model using known physiological properties in order to predict fatigue during nine different submaximal force profiles; consistent with efforts seen in industrial work. We expect this model to be included in digital human modelling software, for the assessment of repetitive work and muscle fatigue in repetitive tasks. SOCIAL MEDIA Summary: The proposed model has applications for estimating task fatigue in proactive ergonomic analyses of complex force patterns using digital human models.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Physical Endurance / Task Performance and Analysis / Workload / Muscle Fatigue / Ergonomics Type of study: Prognostic_studies / Risk_factors_studies Limits: Adult / Female / Humans Language: En Journal: Ergonomics Year: 2016 Document type: Article Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Physical Endurance / Task Performance and Analysis / Workload / Muscle Fatigue / Ergonomics Type of study: Prognostic_studies / Risk_factors_studies Limits: Adult / Female / Humans Language: En Journal: Ergonomics Year: 2016 Document type: Article Country of publication: United kingdom