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ORCIDH-WORKLOAD 2019: Rome, Italy
- Luca Longo
, Maria Chiara Leva:
Human Mental Workload: Models and Applications - Third International Symposium, H-WORKLOAD 2019, Rome, Italy, November 14-15, 2019, Proceedings. Communications in Computer and Information Science 1107, Springer 2019, ISBN 978-3-030-32422-3
Models
- Fabio Babiloni:
Mental Workload Monitoring: New Perspectives from Neuroscience. 3-19 - Aneta Kartali, Milica M. Jankovic, Ivan Gligorijevic, Pavle Mijovic, Bogdan Mijovic, Maria Chiara Leva:
Real-Time Mental Workload Estimation Using EEG. 20-34 - Andrew P. Smith:
Student Workload, Wellbeing and Academic Attainment. 35-47 - Enrique Muñoz-de-Escalona, José Juan Cañas, Jair van Nes:
Task Demand Transition Rates of Change Effects on Mental Workload Measures Divergence. 48-65 - Bethany K. Bracken, Calvin Leather, E. Vincent Cross II, Jerri Stephenson, Maya Greene, Jeffrey A. Lancaster, Brandin Munson, Kritina Holden:
Validation of a Physiological Approach to Measure Cognitive Workload: CAPT PICARD. 66-84 - Patricia López de Frutos, Rubén Rodríguez Rodríguez, Danlin Zheng Zhang, Shutao Zheng, José Juan Cañas, Enrique Muñoz-de-Escalona:
COMETA: An Air Traffic Controller's Mental Workload Model for Calculating and Predicting Demand and Capacity Balancing. 85-104 - Gianluca Di Flumeri, Pietro Aricò, Gianluca Borghini, Nicolina Sciaraffa, Vincenzo Ronca, Alessia Vozzi, Silvia Francesca Storti, Gloria Menegaz, Paolo Fiorini, Fabio Babiloni:
EEG-Based Workload Index as a Taxonomic Tool to Evaluate the Similarity of Different Robot-Assisted Surgery Systems. 105-117
Applications
- Mir Riyanul Islam, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Gianluca Di Flumeri:
Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers' Mental Workload Classification. 121-135 - Bujar Raufi:
Hybrid Models of Performance Using Mental Workload and Usability Features via Supervised Machine Learning. 136-155 - Alexandre Kostenko, Philippe Rauffet, Sorin Moga, Gilles Coppin:
Operator Functional State: Measure It with Attention Intensity and Selectivity, Explain It with Cognitive Control. 156-169 - Nicolina Sciaraffa, Pietro Aricò, Gianluca Borghini, Gianluca Di Flumeri, Antonio Di Florio, Fabio Babiloni:
On the Use of Machine Learning for EEG-Based Workload Assessment: Algorithms Comparison in a Realistic Task. 170-185 - Omolaso Omosehin, Andrew P. Smith:
Do Cultural Differences Play a Role in the Relationship Between Time Pressure, Workload and Student Well-Being? 186-204 - Piero Maggi, Orlando Ricciardi, Francesco Di Nocera:
Ocular Indicators of Mental Workload: A Comparison of Scanpath Entropy and Fixations Clustering. 205-212 - Anja K. Faulhaber, Maik B. Friedrich:
Eye-Tracking Metrics as an Indicator of Workload in Commercial Single-Pilot Operations. 213-225 - Ennia Mariapaola Acerra, Margherita Pazzini, Navid Ghasemi, Valeria Vignali, Claudio Lantieri, Andrea Simone, Gianluca Di Flumeri, Pietro Aricò, Gianluca Borghini, Nicolina Sciaraffa, Paola Lanzi, Fabio Babiloni:
EEG-Based Mental Workload and Perception-Reaction Time of the Drivers While Using Adaptive Cruise Control. 226-239
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