Abstract
Construction workers' valence, which is an important dimension of emotions by representing intrinsic attractiveness and aversiveness, significantly influences their awareness, attention, motivation, etc. Recently, a wearable electroencephalogram (EEG) device has opened a door to measure and understand construction workers' valence levels at the workplace. However, acquiring high quality EEG signals is very difficult at the field due to signal artefacts prevalent in construction sites. In this regard, a signal processing framework was previously developed by the authors to remove the most common artefacts recorded in the EEG signals. In this paper, we further demonstrate how construction workers' valence can be identified by applying this framework. Significant differences in the valence levels were captured while subjects were working in various real work conditions (e.g., working at ground level, top of the ladder, and in confined space). The results show the feasibility of using a wearable EEG device to monitor a worker's valence.
Original language | English |
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Title of host publication | Computing in Civil Engineering 2017 |
Subtitle of host publication | Sensing, Simulation, and Visualization - Selected Papers from the ASCE International Workshop on Computing in Civil Engineering 2017 |
Editors | Ken-Yu Lin, Nora El-Gohary, Pingbo Tang |
Publisher | American Society of Civil Engineers (ASCE) |
Pages | 99-106 |
Number of pages | 8 |
ISBN (Electronic) | 9780784480830 |
DOIs | |
State | Published - 2017 |
Event | 2017 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2017 - Seattle, United States Duration: 25 Jun 2017 → 27 Jun 2017 |
Publication series
Name | Congress on Computing in Civil Engineering, Proceedings |
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Volume | 2017-June |
Conference
Conference | 2017 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2017 |
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Country/Territory | United States |
City | Seattle |
Period | 25/06/17 → 27/06/17 |
Bibliographical note
Publisher Copyright:© 2017 ASCE.
Keywords
- Construction workers' emotion
- EEG artefacts
- Electroencephalogram
- Valence