How the workload impacts on cognitive cooperation: A pilot study

Nicolina Sciaraffa, Gianluca Borghini, Pietro Arico, Gianluca Di Flumeri, Jlenia Toppi, Alfredo Colosimo, Anastatios Bezerianos, Nitish V. Thakor, Fabio Babiloni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cooperation degradation can be seen as one of the main causes of human errors. Poor cooperation could arise from aberrant mental processes, such as mental overload, that negatively affect the user's performance. Using different levels of difficulty in a cooperative task, we combined behavioural, subjective and neurophysiological data with the aim to i) quantify the mental workload under which the crew was operating, ii) evaluate the degree of their cooperation, and iii) assess the impact of the workload demands on the cooperation levels. The combination of such data showed that high workload demand impacted significantly on the performance, workload perception, and degree of cooperation.

Original languageEnglish (US)
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3961-3964
Number of pages4
ISBN (Electronic)9781509028092
DOIs
StatePublished - Sep 13 2017
Externally publishedYes
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: Jul 11 2017Jul 15 2017

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
CountryKorea, Republic of
CityJeju Island
Period7/11/177/15/17

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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