کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
246299 | 502359 | 2016 | 11 صفحه PDF | دانلود رایگان |
• This study develops a wearable EEG monitoring safety helmet.
• There exist distinctive signal patterns at different levels of risks.
• Mental workload is a meaningful indicator of individual vulnerability.
• Brainwave frequency bands can be used to assess mental workload.
Construction companies can accrue losses due to labor fatalities and injuries. Since more than 70% of all accidents are related to human activities, detecting and mitigating human-related risks hold the key to improving the safety conditions within the construction industry. Previous research has revealed that the psychological and emotional conditions of workers can contribute to fatalities and injuries. Recent observations in the area of neural science and psychology suggest that inattentional blindness is one major cause of unexpected human related accidents. Due to the limitation of human mental workload, laborers are vulnerable to unexpected hazards while focusing on complicated construction tasks. Therefore, the ability to detect the mental conditions of workers could reduce unexpected injuries. However, there are currently no available measurement approaches or devices capable of monitoring construction workers' mental conditions. The research proposed in this paper aims to develop a measurement approach to evaluate hazards through neural time–frequency analysis. The experimental results show that neural signals are valid for mental load assessment of construction workers, especially the low frequency bands signals. The research also describes the development of a prototype for a wearable electroencephalography (EEG) safety helmet that enables the collection of the neural information required as input for the measurement approach.
Journal: Automation in Construction - Volume 63, March 2016, Pages 173–183