Title
Automatic feedback on cognitive load and emotional state of traffic controllers
Author
Neerincx, M.A.
Harbers, M.
Lim, D.
van der Tas, V.
Publication year
2014
Abstract
Workload research in command, information and process-control centers, resulted in a modular and formal Cognitive Load and Emotional State (CLES) model with transparent and easy-to-modify classification and assessment techniques. The model distinguishes three representation and analysis layers with an increasing level of abstraction, focusing on respectively the sensing, modeling, and reasoning. Fuzzy logic and its (membership) rules are generated to map a set of values to a cognitive and emotional state (modeling), and to detect surprises of anomalies (reasoning). The models and algorithms allow humans to remain in the loop of workload assessments and distributions, an important resilience requirement of human-automation teams. By detecting unexpected changes (surprises and anomalies) and the corresponding cognition-emotion- performance dependencies, the CLES monitor is expected to improve team's responsiveness to new situations. © 2014 Springer International Publishing.
Subject
Human Performances
PCS - Perceptual and Cognitive Systems
ELSS - Earth, Life and Social Sciences
Informatics
affective computing
electronic partners
resilience engineering
traffic management
workload
Fuzzy logic
Human computer interaction
Affective Computing
electronic partners
Resilience engineerings
Traffic management
workload
Feedback
To reference this document use:
http://resolver.tudelft.nl/uuid:92634465-fb07-41ca-af44-33e0f3cb4e7c
DOI
https://doi.org/10.1007/978-3-319-07515-0_5
TNO identifier
513330
Publisher
Springer Verlag
ISBN
9783319075143
ISSN
1611-3349
Source
11th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2014, Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014, 22 - 27 June 2014, Heraklion, Crete, 8532 LNAI, 42-49
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Document type
conference paper