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Human Mental Workload: Models and Applications

Overview of attention for book
Cover of 'Human Mental Workload: Models and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Mental Workload Monitoring: New Perspectives from Neuroscience
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    Chapter 2 Real-Time Mental Workload Estimation Using EEG
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    Chapter 3 Student Workload, Wellbeing and Academic Attainment
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    Chapter 4 Task Demand Transition Rates of Change Effects on Mental Workload Measures Divergence
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    Chapter 5 Validation of a Physiological Approach to Measure Cognitive Workload: CAPT PICARD
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    Chapter 6 COMETA: An Air Traffic Controller’s Mental Workload Model for Calculating and Predicting Demand and Capacity Balancing
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    Chapter 7 EEG-Based Workload Index as a Taxonomic Tool to Evaluate the Similarity of Different Robot-Assisted Surgery Systems
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    Chapter 8 Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers’ Mental Workload Classification
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    Chapter 9 Hybrid Models of Performance Using Mental Workload and Usability Features via Supervised Machine Learning
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    Chapter 10 Operator Functional State: Measure It with Attention Intensity and Selectivity, Explain It with Cognitive Control
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    Chapter 11 On the Use of Machine Learning for EEG-Based Workload Assessment: Algorithms Comparison in a Realistic Task
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    Chapter 12 Do Cultural Differences Play a Role in the Relationship Between Time Pressure, Workload and Student Well-Being?
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    Chapter 13 Ocular Indicators of Mental Workload: A Comparison of Scanpath Entropy and Fixations Clustering
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    Chapter 14 Eye-Tracking Metrics as an Indicator of Workload in Commercial Single-Pilot Operations
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    Chapter 15 EEG-Based Mental Workload and Perception-Reaction Time of the Drivers While Using Adaptive Cruise Control
Attention for Chapter 8: Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers’ Mental Workload Classification
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Citations

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28 Mendeley
Summary Dimensions citations
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Chapter title
Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers’ Mental Workload Classification
Chapter number 8
Book title
Human Mental Workload: Models and Applications
DOI 10.1007/978-3-030-32423-0_8
Book ISBNs
978-3-03-032422-3, 978-3-03-032423-0
Authors

Islam, Mir Riyanul, Barua, Shaibal, Ahmed, Mobyen Uddin, Begum, Shahina, Flumeri, Gianluca

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 14%
Student > Ph. D. Student 4 14%
Student > Doctoral Student 2 7%
Unspecified 2 7%
Lecturer 2 7%
Other 1 4%
Unknown 13 46%
Readers by discipline Count As %
Computer Science 4 14%
Engineering 3 11%
Unspecified 2 7%
Psychology 1 4%
Arts and Humanities 1 4%
Other 2 7%
Unknown 15 54%

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