Assessment of Construction Workers’ Spontaneous Mental Fatigue Based on Non-Invasive and Multimodal In-Ear EEG Sensors

Author:

Fang Xin1,Li Heng1ORCID,Ma Jie1,Xing Xuejiao2,Fu Zhibo3,Antwi-Afari Maxwell Fordjour4ORCID,Umer Waleed5

Affiliation:

1. Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon 999077, Hong Kong

2. School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, China

3. MindAmp Limited, Central and West District, Admiralty 999077, Hong Kong

4. Department of Civil Engineering, College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK

5. Department of Architecture and Built Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK

Abstract

Construction activities are often conducted in outdoor and harsh environments and involve long working hours and physical and mental labor, which can lead to significant mental fatigue among workers. This study introduces a novel and non-invasive method for monitoring and assessing mental fatigue in construction workers. Based on cognitive neuroscience theory, we analyzed the neurophysiological mapping of spontaneous mental fatigue and developed multimodal in-ear sensors specifically designed for construction workers. These sensors enable real-time and continuous integration of neurophysiological signals. A cognitive experiment was conducted to validate the proposed mental fatigue assessment method. Results demonstrated that all selected supervised classification models can accurately identify mental fatigue by using the recorded neurophysiological data, with evaluation metrics exceeding 80%. The long short-term memory model achieved an average accuracy of 92.437%. This study offers a theoretical framework and a practical approach for assessing the mental fatigue of on-site workers and provides a basis for the proactive management of occupational health and safety on construction sites.

Funder

Humanities and Social Sciences Fund of the Education Ministry of China

China Postdoctoral Science Foundation

Publisher

MDPI AG

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