Ergonomics and Machine Learning: Wearable Sensors in the Prevention of Work-Related Musculoskeletal Disorders

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

One of the biggest challenges of the labor world is to ensure the health and well-being of the workers. Preventing work-related musculoskeletal disorders (WRMSDs) is increasingly relevant across all sectors. In recent studies, there has been a growing application of machine learning and sensory technology to develop strategies for ergonomic risk detection and prevention of WRMSDs in the short and long term. The use of wearable sensors allows real-time monitoring of workers’ postures, and has proven to be an asset for ergonomic studies due to its high accuracy. In addition to preventive applications, machine learning can increase workers’ productivity and safety. Despite being an area that shows great potential, it still has some limitations and opportunities for development. This literature review was carried out in a structured and systematic way based on the defined inclusion criteria and keywords chosen. Fifteen articles published between 2017 and 2022 were analyzed. This paper aims to study the current state of the use of the application of wearable sensors in Ergonomics and identify the challenges that this technology faces in the future.

Original languageEnglish
Title of host publicationOccupational and Environmental Safety and Health IV
EditorsPedro M. Arezes, J. Santos Baptista, Rui B. Melo, Jacqueline Castelo Branco, Paula Carneiro, Ana Colim, Nélson Costa, Susana Costa, J. Duarte, J. C. Guedes, Gonçalo Perestrelo
Place of PublicationCham
PublisherSpringer
Pages199-210
Number of pages12
ISBN (Electronic)978-3-031-12547-8
ISBN (Print)978-3-031-12546-1, 978-3-031-12549-2
DOIs
Publication statusPublished - 17 Sept 2022

Publication series

NameStudies in Systems, Decision and Control
PublisherSpringer
Volume449
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

Keywords

  • Ergonomics
  • Machine learning
  • Wearable sensors
  • WRMSDs

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