Measuring and Computing Cognitive Statuses of Construction Workers Based on Electroencephalogram: A Critical Review
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Measuring and Computing Cognitive Statuses of Construction Workers Based on Electroencephalogram: A Critical Review
Authors
Keywords
-
Journal
IEEE Transactions on Computational Social Systems
Volume 9, Issue 6, Pages 1644-1659
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Online
2022-04-08
DOI
10.1109/tcss.2022.3158585
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Relationship between rework of engineering drawing tasks and stress level measured from physiological signals
- (2021) Jeonghyeun Chae et al. AUTOMATION IN CONSTRUCTION
- Monitoring distraction of construction workers caused by noise using a wearable Electroencephalography (EEG) device
- (2021) Jinjing Ke et al. AUTOMATION IN CONSTRUCTION
- EEG Driving Fatigue Detection With PDC-Based Brain Functional Network
- (2021) Fei Wang et al. IEEE SENSORS JOURNAL
- Assessment of noise annoyance level of shield tunneling machine drivers under noisy environments based on combined physiological activities
- (2021) Xuejiao Xing et al. APPLIED ACOUSTICS
- Feasibility Study to Identify Brain Activity and Eye-Tracking Features for Assessing Hazard Recognition Using Consumer-Grade Wearables in an Immersive Virtual Environment
- (2021) Mojtaba Noghabaei et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Paving the Way for Future EEG Studies in Construction: Dependent Component Analysis for Automatic Ocular Artifact Removal from Brainwave Signals
- (2021) Yizhi Liu et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Classification of construction hazard-related perceptions using: Wearable electroencephalogram and virtual reality
- (2021) JungHo Jeon et al. AUTOMATION IN CONSTRUCTION
- Applications of electroencephalography in construction
- (2021) Sina Saedi et al. AUTOMATION IN CONSTRUCTION
- The effect of noise content and level on cognitive performance measured by electroencephalography (EEG)
- (2021) Jinjing Ke et al. AUTOMATION IN CONSTRUCTION
- Passenger overall comfort in high-speed railway environments based on EEG: Assessment and degradation mechanism
- (2021) Yong Peng et al. BUILDING AND ENVIRONMENT
- Comprehensive assessment of embodied environmental impacts of buildings using normalized environmental impact factors
- (2021) Baoquan Cheng et al. Journal of Cleaner Production
- Semantic-Aware Dehazing Network With Adaptive Feature Fusion
- (2021) Shengdong Zhang et al. IEEE Transactions on Cybernetics
- Using Electroencephalography (EEG) Power Responses to Investigate the Effects of Ambient Oxygen Content, Safety Shoe Type, and Lifting Frequency on the Worker’s Activities
- (2020) Mohamed Z. Ramadan et al. Biomed Research International
- Is the Chinese construction industry moving towards a knowledge- and technology-intensive industry?
- (2020) Yuhe Wang et al. JOURNAL OF CLEANER PRODUCTION
- Effects of physical fatigue on the induction of mental fatigue of construction workers: A pilot study based on a neurophysiological approach
- (2020) Xuejiao Xing et al. AUTOMATION IN CONSTRUCTION
- Online Learning Algorithms
- (2020) Nicolò Cesa-Bianchi et al. Annual Review of Statistics and Its Application
- Detecting Fatigue Status of Pilots Based on Deep Learning Network Using EEG Signals
- (2020) Edmond Q. wu et al. IEEE Transactions on Cognitive and Developmental Systems
- A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving
- (2019) Monika Lohani et al. Frontiers in Human Neuroscience
- EEG Source Imaging: A Practical Review of the Analysis Steps
- (2019) Christoph M. Michel et al. Frontiers in Neurology
- A multicomponent and neurophysiological intervention for the emotional and mental states of high-altitude construction workers
- (2019) Xuejiao Xing et al. AUTOMATION IN CONSTRUCTION
- Pre-service fatigue screening for construction workers through wearable EEG-based signal spectral analysis
- (2019) Heng Li et al. AUTOMATION IN CONSTRUCTION
- A novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN
- (2019) Yimin Hou et al. Journal of Neural Engineering
- Scoping Review of EEG Studies in Construction Safety
- (2019) Yamei Zhang et al. International Journal of Environmental Research and Public Health
- Using EEG for Mental Fatigue Assessment: A Comprehensive Look Into the Current State of the Art
- (2019) Thiago Gabriel Monteiro et al. IEEE Transactions on Human-Machine Systems
- Consumer Grade EEG Measuring Sensors as Research Tools: A Review
- (2019) Phattarapong Sawangjai et al. IEEE SENSORS JOURNAL
- EEG-based workers' stress recognition at construction sites
- (2018) Houtan Jebelli et al. AUTOMATION IN CONSTRUCTION
- Performance Assessment in Complex Engineering Projects Using a System-of-Systems Framework
- (2018) Jin Zhu et al. IEEE Systems Journal
- Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?
- (2018) Stefano A. Bini JOURNAL OF ARTHROPLASTY
- EEG Signal-Processing Framework to Obtain High-Quality Brain Waves from an Off-the-Shelf Wearable EEG Device
- (2018) Houtan Jebelli et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Measuring Workers’ Emotional State during Construction Tasks Using Wearable EEG
- (2018) Sungjoo Hwang et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- EEGNet: a compact convolutional neural network for EEG-based brain--computer interfaces
- (2018) Vernon Lawhern et al. Journal of Neural Engineering
- A Review of Emotion Recognition Using Physiological Signals
- (2018) Lin Shu et al. SENSORS
- Measuring Workers’ Emotional State during Construction Tasks Using Wearable EEG
- (2018) Sungjoo Hwang et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Influence Mechanism of Construction Workers' Safety Psychology on their Safety Behavior Based on Event-related Potentials
- (2018) Qing Liu NeuroQuantology
- A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multi-Task Learning Algorithms (OMTL)
- (2018) Houtan Jebelli et al. IEEE Journal of Biomedical and Health Informatics
- LSTM-Based EEG Classification in Motor Imagery Tasks
- (2018) Ping Wang et al. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
- Detecting and measuring construction workers' vigilance through hybrid kinematic-EEG signals
- (2018) Di Wang et al. AUTOMATION IN CONSTRUCTION
- Assessing Task Mental Workload in Construction Projects: A Novel Electroencephalography Approach
- (2017) Jiayu Chen et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Development of a Stressors–Stress–Performance–Outcome Model for Expatriate Construction Professionals
- (2017) Mei-yung Leung et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Assessing Task Mental Workload in Construction Projects: A Novel Electroencephalography Approach
- (2017) Jiayu Chen et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Development of a Stressors–Stress–Performance–Outcome Model for Expatriate Construction Professionals
- (2017) Mei-yung Leung et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Correlative Evaluation of Mental and Physical Workload of Laparoscopic Surgeons Based on Surface Electromyography and Eye-tracking Signals
- (2017) Jian-Yang Zhang et al. Scientific Reports
- Revealing the “Invisible Gorilla” in construction: Estimating construction safety through mental workload assessment
- (2016) Jiayu Chen et al. AUTOMATION IN CONSTRUCTION
- Signal Quality Assessment Model for Wearable EEG Sensor on Prediction of Mental Stress
- (2015) Bin Hu et al. IEEE TRANSACTIONS ON NANOBIOSCIENCE
- EEG artifact removal—state-of-the-art and guidelines
- (2015) Jose Antonio Urigüen et al. Journal of Neural Engineering
- Deep learning
- (2015) Yann LeCun et al. NATURE
- A Review of Ensemble Learning Based Feature Selection
- (2014) Donghai Guan et al. IETE TECHNICAL REVIEW
- The urban brain: analysing outdoor physical activity with mobile EEG
- (2013) Peter Aspinall et al. BRITISH JOURNAL OF SPORTS MEDICINE
- Artifact Removal in Physiological Signals—Practices and Possibilities
- (2012) K. T. Sweeney et al. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
- Team Processes and Safety of Workers: Cognitive, Affective, and Behavioral Processes of Construction Crews
- (2012) Panagiotis Mitropoulos et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Task Demands in Masonry Work: Sources, Performance Implications, and Management Strategies
- (2012) Panagiotis Mitropoulos et al. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
- Understanding End-Users’ Acceptance of Enterprise Resource Planning (ERP) System in Project-Based Sectors
- (2011) Young Hoon Kwak et al. IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
- Modeling of the human skull in EEG source analysis
- (2010) Moritz Dannhauer et al. HUMAN BRAIN MAPPING
- On Complexity Issues of Online Learning Algorithms
- (2010) Yuan Yao IEEE TRANSACTIONS ON INFORMATION THEORY
- Processing Expectancy Violations during Music Performance and Perception: An ERP Study
- (2009) Clemens Maidhof et al. JOURNAL OF COGNITIVE NEUROSCIENCE
- The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging
- (2009) S. Vulliemoz et al. NEUROIMAGE
- Helmet-based physiological signal monitoring system
- (2008) Youn Sung Kim et al. EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY
- Classifying mental tasks based on features of higher-order statistics from EEG signals in brain–computer interface
- (2007) Shang-Ming Zhou et al. INFORMATION SCIENCES
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started