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Abstract
Inappropriate task allocation in construction activities results not only in lower productivity but also higher error rates and more work-related injuries. Without quantitative assessment of task demand, it is nearly impossible to achieve reasonable and flexible task allocation. However, it is extremely difficult to assess the mental/cognitive demand of construction tasks quantitatively and reliably. This paper introduces a novel electroencephalography (EEG) approach to estimate task mental workload based on the power spectral densities (PSDs) of major frequency bands. A preliminary experiment was designed and conducted to demonstrate the proposed assessment approach, and the National Aeronautics and Space Administration task load index (NASA-TLX) was adopted to validate the results. Four EEG channels were tested for 30 subjects in the preliminary experiment with three-way analysis of variance (ANOVA). Both the types of construction activities and frequency bands show statistically significant effects on PSDs of the EEG signals. Among all channels, the channel that is located at the left frontal parietal lobe (Fp1), especially the gamma band, showed the highest correlation with the mental load level. The final statistical results and the frequency bin model suggest that the estimation results are consistent with the NASA-TLX mental demand scores.
| Original language | English |
|---|---|
| Article number | 04017053 |
| Journal | Journal of Construction Engineering and Management |
| Volume | 143 |
| Issue number | 8 |
| Online published | 30 May 2017 |
| DOIs | |
| Publication status | Published - Aug 2017 |
Research Keywords
- Construction tasks
- Electroencephalography (EEG)
- Labor and personnel issues
- Task allocation
- Task mental workload
RGC Funding Information
- RGC-funded
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Dive into the research topics of 'Assessing Task Mental Workload in Construction Projects: A Novel Electroencephalography Approach'. Together they form a unique fingerprint.Projects
- 1 Finished
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ECS: Mitigating Human-related Hazards in Construction Projects: An Agile Framework for Jobsite Safety Assessment through Integrating Multiple Data Sources
CHEN, J. (Principal Investigator / Project Coordinator)
1/01/17 → 24/06/21
Project: Research
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