Measuring Workers' Emotional State during Construction Tasks Using Wearable EEG

Sungjoo Hwang, Houtan Jebelli, Byungjoo Choi, Minji Choi, Sanghyun Lee

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Construction workers' emotional states (e.g., pleasure, displeasure, excitement, and relaxation) are known as a critical factor that affect their performance (e.g., safety, health, and productivity). To prevent adverse impacts on work performance, measuring emotional states should take precedence to better understand how workers' emotions vary while they are working. Among many methods available to measure emotional states, electroencephalogram (EEG) has a great potential for quantitative measurement by overcoming a possible bias from the survey-based subjective assessment of emotions. Although EEG-based emotion measurement has been tested and applied only in a laboratory environment, recent advancements in wearable EEG sensors, which are portable, wireless, and affordable, open a new door toward nonintrusive field emotion measurement. This study thus investigates the feasibility of measuring workers' emotions in the field using a wearable EEG sensor. To do this, a bipolar dimensional emotion model, which consists of valence (from displeasure to pleasure) and arousal (from relaxation to excitement) dimensions, was applied to quantify workers' emotional states. Then, workers' valence and arousal levels were measured using a wearable EEG sensor during their ongoing tasks. The validity of the EEG-based emotion measurement was examined through a comparison with cortisol levels obtained from workers' saliva samples, which has been accepted as a reliable physical measure of emotions. The results demonstrate the applicability of a wearable EEG sensor for measuring workers' emotions, particularly valence levels, which remain crucial to understanding workers' emotional states. This study contributes to the body of knowledge on in-depth studies for understanding workers' emotions in the field by providing a means to continuously and nonintrusively measure workers' emotions while they are working.

Original languageEnglish (US)
Article number04018050
JournalJournal of Construction Engineering and Management
Volume144
Issue number7
DOIs
StatePublished - Jul 1 2018

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Industrial relations
  • Strategy and Management

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