Work

Improving dynamic endurance time predictions for shoulder fatigue: A comparative evaluation

Year: 2025

Type: article

Abstract: Work-related musculoskeletal disorders (WMSDs) are commonplace in industry and a host of qualitative and quantitative approaches have been used to assuage the problem, including wearable sensors and biomechanical endurance models, both of which are used in the present study. Six endurance models (consumed endurance, new improved consumed endurance (NICE) and Frey-Avin general and shoulder models) with four alternative maximum torque quantification methods, including a novel approach to generate maximum torque, are compared. The proposed approach to quantify maximum torque, in combination with the NICE produced the lowest root mean square errors (RMSE), indicating improved performance compared to the literature. The mean RMSE was reduced from 41.08s to 19.11s for all subjects, from 26.13s to 12.16s for males (R2 = .459), and 51.28s to 24.45s for females (R2 = .314) using the proposed method. This research provides an optimised and individualised endurance prediction approach for loaded dynamic movements which can be applied to industry tasks, and aid in reducing the prevalence of WMSDs.

Source: Applied Ergonomics

DOI: 10.1016/j.apergo.2025.104480

Authors: Patricia O'Sullivan, Matteo Menolotto, Brendan O'Flynn, Dimitrios-Sokratis Komaris

Institutions: University College Cork, Tyndall National Institute, Centre for Research and Technology Hellas

Language: English

Topic: Ergonomics and Musculoskeletal Disorders

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,400