Human Mental Workload: Models and Applications: Third International Symposium, H-WORKLOAD 2019, Rome, Italy, November 14–15, 2019, Proceedings

Description

This book constitutes the refereed proceedings of the Third International Symposium on Human Mental Workload: Models and Applications, H-WORKLOAD 2019, held in Rome, Italy, in November 2019. The volume presents one keynote paper as well as 14 revised full papers, which were carefully reviewed and selected from 32 submissions. The papers are organized in two topical sections on models and applications. Front Matter ....Pages i-xiii Front Matter ....Pages 1-1 Mental Workload Monitoring: New Perspectives from Neuroscience (Fabio Babiloni)....Pages 3-19 Real-Time Mental Workload Estimation Using EEG (Aneta Kartali, Milica M. Janković, Ivan Gligorijević, Pavle Mijović, Bogdan Mijović, Maria Chiara Leva)....Pages 20-34 Student Workload, Wellbeing and Academic Attainment (Andrew P. Smith)....Pages 35-47 Task Demand Transition Rates of Change Effects on Mental Workload Measures Divergence (Enrique Muñoz-de-Escalona, José Juan Cañas, Jair van Nes)....Pages 48-65 Validation of a Physiological Approach to Measure Cognitive Workload: CAPT PICARD (Bethany Bracken, Calvin Leather, E. Vincent Cross II, Jerri Stephenson, Maya Greene, Jeff Lancaster et al.)....Pages 66-84 COMETA: An Air Traffic Controller’s Mental Workload Model for Calculating and Predicting Demand and Capacity Balancing (Patricia López de Frutos, Rubén Rodríguez Rodríguez, Danlin Zheng Zhang, Shutao Zheng, José Juan Cañas, Enrique Muñoz-de-Escalona)....Pages 85-104 EEG-Based Workload Index as a Taxonomic Tool to Evaluate the Similarity of Different Robot-Assisted Surgery Systems (Gianluca Di Flumeri, Pietro Aricò, Gianluca Borghini, Nicolina Sciaraffa, Vincenzo Ronca, Alessia Vozzi et al.)....Pages 105-117 Front Matter ....Pages 119-119 Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers’ Mental Workload Classification (Mir Riyanul Islam, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Gianluca Di Flumeri)....Pages 121-135 Hybrid Models of Performance Using Mental Workload and Usability Features via Supervised Machine Learning (Bujar Raufi)....Pages 136-155 Operator Functional State: Measure It with Attention Intensity and Selectivity, Explain It with Cognitive Control (Alexandre Kostenko, Philippe Rauffet, Sorin Moga, Gilles Coppin)....Pages 156-169 On the Use of Machine Learning for EEG-Based Workload Assessment: Algorithms Comparison in a Realistic Task (Nicolina Sciaraffa, Pietro Aricò, Gianluca Borghini, Gianluca Di Flumeri, Antonio Di Florio, Fabio Babiloni)....Pages 170-185 Do Cultural Differences Play a Role in the Relationship Between Time Pressure, Workload and Student Well-Being? (Omolaso Omosehin, Andrew P. Smith)....Pages 186-204 Ocular Indicators of Mental Workload: A Comparison of Scanpath Entropy and Fixations Clustering (Piero Maggi, Orlando Ricciardi, Francesco Di Nocera)....Pages 205-212 Eye-Tracking Metrics as an Indicator of Workload in Commercial Single-Pilot Operations (Anja K. Faulhaber, Maik Friedrich)....Pages 213-225 EEG-Based Mental Workload and Perception-Reaction Time of the Drivers While Using Adaptive Cruise Control (Ennia Acerra, Margherita Pazzini, Navid Ghasemi, Valeria Vignali, Claudio Lantieri, Andrea Simone et al.)....Pages 226-239 Back Matter ....Pages 241-241