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Titlebook: Human Mental Workload: Models and Applications; Third International Luca Longo,Maria Chiara Leva Conference proceedings 2019 Springer Natu

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书目名称Human Mental Workload: Models and Applications
副标题Third International
编辑Luca Longo,Maria Chiara Leva
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Human Mental Workload: Models and Applications; Third International  Luca Longo,Maria Chiara Leva Conference proceedings 2019 Springer Natu
描述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..
出版日期Conference proceedings 2019
关键词artificial intelligence; classification; classification algorithm; computer networks; education
版次1
doihttps://doi.org/10.1007/978-3-030-32423-0
isbn_softcover978-3-030-32422-3
isbn_ebook978-3-030-32423-0Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Real-Time Mental Workload Estimation Using EEGver, it is thus based on subjective experience. Neuroergonomics tackles this issue, by employing neurophysiological metrics to obtain objective, real-time information. We measured mental workload (MWL) derived from electroencephalography (EEG) signals, for subjects engaged in a simulated computer-ba
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Task Demand Transition Rates of Change Effects on Mental Workload Measures Divergencence the three measures should reflect changes in task-load, one would expect convergence, yet divergence between the measures has been reported. A potential explanation could be related to the differential sensitivity of mental workload measures to rates of change in task-load transitions: some meas
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COMETA: An Air Traffic Controller’s Mental Workload Model for Calculating and Predicting Demand and the air traffic controller (ATCo). As detailed mental pictures can overcome ATCo’s limited attentional resources (causing Mental Overload), she/he can use internal strategies called abstractions to mitigate the cognitive complexity of the control task. This paper gathers the modelling, automation a
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EEG-Based Workload Index as a Taxonomic Tool to Evaluate the Similarity of Different Robot-Assisted and increasing efficiency. This work aimed at proposing an EEG-based neurometric of mental workload, previously validated in other contexts, as a taxonomic tool to evaluate the similarity, in terms of cognitive demands, of two different systems: the da Vinci surgical system, leader in the field of r
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Operator Functional State: Measure It with Attention Intensity and Selectivity, Explain It with Cogned, in terms of dialogue or function allocation. To support this reconfigurable cooperation, a crucial point is to assess online the operator’s ability to keep performing the mission, to anticipate and predict potential future performance impairments, as well as to be able to activate appropriate co
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