2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2015
DOI: 10.1109/embc.2015.7320063
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Reliability over time of EEG-based mental workload evaluation during Air Traffic Management (ATM) tasks

Abstract: Machine-learning approaches for mental workload (MW) estimation by using the user brain activity went through a rapid expansion in the last decades. In fact, these techniques allow now to measure the MW with a high time resolution (e.g. few seconds). Despite such advancements, one of the outstanding problems of these techniques regards their ability to maintain a high reliability over time (e.g. high accuracy of classification even across consecutive days) without performing any recalibration procedure. Such c… Show more

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Cited by 44 publications
(37 citation statements)
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“…More recently, Shou et al (2012) found that “the frontal theta EEG activity was a sensitive and reliable metric to assess workload […] during an ATC task at the resolution of minute (s).” The same findings have been highlighted by Borghini et al (2013) involving pilots in flight simulation tasks. In other recent studies involving ATCOs (Aricò et al, 2013, 2014, 2015b,c; Borghini et al, 2014; Di Flumeri et al, 2015; Toppi et al, 2016), it was demonstrated how it was possible to compute an EEG-based Workload Index able to significantly discriminate the workload demands of the ATM task, and to monitor them continuously by using frontal-parietal brain features. Other studies about the mental workload estimation by using neurophysiological indexes, have been proposed also in other operational contexts (Car drivers - Kohlmorgen et al, 2007; Borghini et al, 2012a; military domain - Dorneich et al, 2005).…”
Section: Introductionmentioning
confidence: 99%
“…More recently, Shou et al (2012) found that “the frontal theta EEG activity was a sensitive and reliable metric to assess workload […] during an ATC task at the resolution of minute (s).” The same findings have been highlighted by Borghini et al (2013) involving pilots in flight simulation tasks. In other recent studies involving ATCOs (Aricò et al, 2013, 2014, 2015b,c; Borghini et al, 2014; Di Flumeri et al, 2015; Toppi et al, 2016), it was demonstrated how it was possible to compute an EEG-based Workload Index able to significantly discriminate the workload demands of the ATM task, and to monitor them continuously by using frontal-parietal brain features. Other studies about the mental workload estimation by using neurophysiological indexes, have been proposed also in other operational contexts (Car drivers - Kohlmorgen et al, 2007; Borghini et al, 2012a; military domain - Dorneich et al, 2005).…”
Section: Introductionmentioning
confidence: 99%
“…The question of reliability of EEG-based workload determination in ATM tasks was examined in Arico et al (2015). According to the authors the reason for the decreasing classification accuracy over days, as reported by Christensen and Estepp (2013), could be overfitting, i.e., a too high specificity of the training data.…”
Section: Introductionmentioning
confidence: 99%
“…This is especially important as frequent allegations were made concerning the time interval between training and test of the classifier that proved to be particular relevant for the classification accuracy . In order to avoid overfitting and increase the stability of the classifier performance over time a smaller number of features could be beneficial (Arico et al, 2015).…”
Section: Introductionmentioning
confidence: 99%
“…good example is the transport domain, where the safety of the passengers is deemed dependent on: the performance of the pilots (G. Borghini et al, 2013;Gianluca Borghini et al, 2016, 2015Dehais et al, 2018;Sciaraffa et al, 2017;Vecchiato et al, 2016); the drivers (Di Flumeri et al, 2018;Maglione et al, 2014); or those within the traffic control rooms (P. Pietro Arico et al, 2015;Pietro Aricò et al, 2016;Gianluca Borghini et al, 2017;di Flumeri et al, 2015). Under such conditions, any human error will potentially lead to drastic and dramatic consequences.…”
Section: Open Access | Mini-review Issn: 2576-828xmentioning
confidence: 99%