Wearable Systems for Assessing Work-Related Risks in Musculoskeletal Disorders
Author Information
Author(s): Motta Filippo, Varrecchia Tiwana, Chini Giorgia, Ranavolo Alberto, Galli Manuela
Primary Institution: Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano
Hypothesis
This systematic review aims to compile research on the use of wearable sensor systems to assess work-related musculoskeletal disorders (WRMSDs).
Conclusion
The review identifies existing research on WRMSD risks utilizing wearable systems in various job sectors and highlights under-researched areas that need further study.
Supporting Evidence
- Work-related musculoskeletal disorders affect 1.71 billion people globally.
- Over 50% of workers report suffering from work-related musculoskeletal disorders.
- Quantitative analysis through sensors can help identify causes of musculoskeletal disorders.
Takeaway
This study looks at how wearable technology can help understand and prevent injuries that workers get from doing their jobs.
Methodology
The study used a systematic review method to gather peer-reviewed publications from databases like PubMed, Web of Science, and Scopus, focusing on studies published between 2000 and 2023.
Potential Biases
The studies often had risks related to selection bias and lack of blinding, as participants were aware of the study's aims.
Limitations
Many studies had small sample sizes and were conducted in laboratory settings rather than real work environments, which may limit the generalizability of the findings.
Digital Object Identifier (DOI)
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