Towards an EEG-Based Approach for Detecting Falls from Height Hazards Using Construction Workers’ Physiological Signals-Reference-Cited by-同舟云学术

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Towards an EEG-Based Approach for Detecting Falls from Height Hazards Using Construction Workers’ Physiological Signals

Published:2024-03-18 Issue: Volume:5 Page:647-656
ISSN:
Container-title:Construction Research Congress 2024
language:
Short-container-title:

Author:

Li Jie¹²³,Ouyang Yewei¹²³,Luo Xiaowei¹²³

Affiliation:

1. Ph.D. Student, Dept. of Architecture and Civil Engineering, City Univ. of Hong Kong, Hong Kong.

2. Ph.D. Candidate, Dept. of Architecture and Civil Engineering, City Univ. of Hong Kong, Hong Kong.

3. Associate Professor, Dept. of Architecture and Civil Engineering, City Univ. of Hong Kong, Hong Kong. ORCID: .

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485293.065

Reference15 articles.

1. Wearable Sensing Technology Applications in Construction Safety and Health

2. Automated detection of construction work at heights and deployment of safety hooks using IMU with a barometer

3. Jebelli H. Khalili M. M. Hwang S. and Lee S. “A supervised learning-based construction workers’ stress recognition using a wearable electroencephalography (EEG) device.” Proc. Construction Research Congress 2018 40–50.

4. Real-time vision-based worker localization & hazard detection for construction

5. Feature extraction and selection for emotion recognition from EEG;Jenke R.;IEEE Trans. Affective Comput,2014

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