Facial Expression Analysis for Cognitive State Estimation in Aerospace Human-Machine Systems

Federico Rivalta, Nichakorn Pongsakornsathien, Alessandro Gardi, Roberto Sabatini, Trevor Kistan, Neta Ezer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Growing air traffic and an increasing demand for Unmanned Aircraft System (UAS) services elicit the need for new systems assisting air traffic controllers and UAS operators in performing their tasks in order to manage more aircraft without compromising operational safety. A key challenge is to support One-To-Many (OTM) operations where a single human operator is responsible for command and control of multiple assets. This study focusses on facial expression analysis for cognitive state estimation in a representative OTM scenario. The aim is to support the design of OTM systems and associated Human-Machine Interfaces and Interaction (HMI2), which can dynamically adapt the automation support level as a function of the operator's cognitive states.

Original languageBritish English
Title of host publicationProceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020
EditorsGiancarlo Fortino, Fei-Yue Wang, Andreas Nurnberger, David Kaber, Rino Falcone, David Mendonca, Zhiwen Yu, Antonio Guerrieri
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728158716
DOIs
StatePublished - Sep 2020
Event1st IEEE International Conference on Human-Machine Systems, ICHMS 2020 - Virtual, Rome, Italy
Duration: 7 Sep 20209 Sep 2020

Publication series

NameProceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020

Conference

Conference1st IEEE International Conference on Human-Machine Systems, ICHMS 2020
Country/TerritoryItaly
CityVirtual, Rome
Period7/09/209/09/20

Keywords

  • Cognitive Workload
  • Decision Making
  • Human-Machine Interface
  • Human-Machine System
  • UAS Traffic Management

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