TY - JOUR
T1 - Measuring Workers' Emotional State during Construction Tasks Using Wearable EEG
AU - Hwang, Sungjoo
AU - Jebelli, Houtan
AU - Choi, Byungjoo
AU - Choi, Minji
AU - Lee, Sanghyun
N1 - Funding Information:
The authors would like to acknowledge their industry partners for their help in data collection, as well as anonymous participants who participated in the data collection. The authors also wish to acknowledge financial support from the University of Michigan Third Century Initiative. Also, the first author wishes to acknowledge financial support by the Ewha Womans University Research Grant of 2017.
Publisher Copyright:
© 2018 American Society of Civil Engineers.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - 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.
AB - 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.
KW - Arousal
KW - Brain waves
KW - Electroencephalogram
KW - Emotions
KW - Neurophysiology
KW - Valence
KW - Wearable devices
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U2 - 10.1061/(ASCE)CO.1943-7862.0001506
DO - 10.1061/(ASCE)CO.1943-7862.0001506
M3 - Article
AN - SCOPUS:85045749859
SN - 0733-9364
VL - 144
JO - Journal of Construction Engineering and Management
JF - Journal of Construction Engineering and Management
IS - 7
M1 - 04018050
ER -