Monitoring Distraction of Construction Workers Using a Wearable Electroencephalography (EEG) Device

Abstract

Distraction is a major cause of unsafe behaviors and decreased safety performance in a high-attention demanding construction environment. However, few studies have drawn attention on cognitive characteristics of distraction and the method to detect it quantitatively. To fill the gap, this study investigates the correlation between distraction and mental activity using EEG device, aiming to provide a real-time approach to monitor the worker’s distraction objectively. In this study, sustained attention to response task (SART) has been employed to induce the occurrences of distraction in the simulated construction safety inspection tasks. The recorded EEG data was divided into two groups corresponding with task performance: focused and distracted. By analyzing the data through pre-processing and feature extraction methods, the objective is to examine indices that enable to distinguish these two statuses based on time and frequency domain. The metrics proposed are estimated to be associated with cognitive functions like attention deficit and attention allocation, herein serve as an objective assessment of an individual’s sustained attention degrees and cognitive failures. Accordingly, this study facilitated the development of cognitive features of distraction theoretically and made it possible to detect and control the inner distraction leading to unsafe behavior or decreased task performance in practice.