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Worker Customized Stress Monitoring through Body Composition Analysis and Wearable Bio-Sensor

  • Junhee JUNG (School of Architecture & Building Sciences, Chung-Ang University) ;
  • Seohyun YANG (School of Architecture & Building Sciences, Chung-Ang University) ;
  • Emmanuel KIMITO (School of Architecture & Building Sciences, Chung-Ang University) ;
  • Dohyeong KIM (School of Architecture & Building Sciences, Chung-Ang University) ;
  • Chansik PARK (School of Architecture & Building Sciences, Chung-Ang University) ;
  • Dongmin LEE (School of Architecture & Building Sciences, Chung-Ang University)
  • Published : 2024.07.29

Abstract

Recent wearable devices can measure workers' physical and mental stress levels in the workplace, enabling timely interventions or adjustments to improve safety, well-being, and productivity. However, stress is a subjective metric, response and recovery from stress varies depending on the individual's physical condition. This study is a preliminary study to test whether there are relationships between stress and physical conditions (i.e., body compositions) of individual workers. To find the relationship between various body compositions of the participants and their stress levels, Spearman correlation coefficients and linear regression analysis were conducted. The results showed a significant relationship between workers' stress level and their body composition. This suggests that by utilizing easily measurable body composition, customized stress monitoring for individual workers can be achieved, contributing to the prevention of construction accidents and the creation of a safer construction site.

Keywords

Acknowledgement

This research was conducted with the support of the "National R&D Project for Smart Construction Technology (No.RS-2020-KA156291)" funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation. Additionally, this research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00217322 and No. NRF-2022R1A2B5B02002553).

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