Analysis of Biometric Sensor Data for Predicting Fatigue: A Framework Towards Reducing Work-Related Musculoskeletal Disorders in Aviation Manufacturing Workers

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov:2021:6928-6932. doi: 10.1109/EMBC46164.2021.9631033.

Abstract

Work-Related Musculoskeletal Disorders (WMSDs) transpire when injuries to the musculoskeletal system (e.g. muscles, ligaments, tendons, and nerves) occur due to high fatigue inducing work-related activities, where repetitive movements and muscle strain are prevalent. However, it is challenging to quantify the risk of injury due to the assortment of tasks that factory workers may perform. Nevertheless, wearable sensors are a viable outlet that can unobtrusively capture biometric data in order to calculate objective measures, such as fatigue, which increases the risk of developing WMSDs. This paper presents a novel wearable sensor-based ergonomic monitoring system (ErgoRelief), which has been designed to predict fatigue within the context of aviation factory work. An experiment has been undertaken whereby thirty participants completed a series of repetitive tasks whilst wearing our sensor system. Results of multiple linear regression models demonstrate a maximum Adjusted R2 Score of 0.9259.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aviation*
  • Biometry
  • Fatigue / diagnosis
  • Humans
  • Musculoskeletal Diseases* / diagnosis
  • Musculoskeletal Diseases* / prevention & control
  • Risk Factors