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Investigating Cognitive Load in Emergency Control Room Simulations

dc.contributor.authorPöhler, Jonas
dc.contributor.authorVitt, Antonia
dc.contributor.authorFlegel, Nadine
dc.contributor.authorMentler, Tilo
dc.contributor.authorvan Laerhoven, Kristof
dc.date.accessioned2023-08-24T06:24:27Z
dc.date.available2023-08-24T06:24:27Z
dc.date.issued2023
dc.description.abstractWe propose a novel approach to measure cognitive load in emergency control room operators using their breathing patterns. By using LstSim, a community-driven emergency control room simulator, we aim to recreate the work environment of a dispatcher, induce a cognitive load, and measure the response in the user’s breathing. Participants were monitored and recorded through wearable sensors, depth cameras below the screens, and simulation-internal parameters and interactions. The participants’ breathing patterns were analyzed to identify changes in breathing amplitude in response to varying levels of cognitive load. The results of our study provide compelling evidence that a simulated control room environment is successful in inducing cognitive load on participants shown in a significant increase in NASA TLX scores as well as a 13% increase in breathing amplitude. Despite the challenges posed by this individual variability, our findings also highlight the potential of using breathing as a real-time, noninvasive measure of cognition in control rooms. This has significant implications for the design and operation of emergency control rooms, potentially leading to the development of more responsive systems that adapt to the operator’s cognition load, thereby enhancing performance and effectiveness.de
dc.identifier.doi10.18420/muc2023-mci-ws01-355
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/42097
dc.publisherGI
dc.relation.ispartofMensch und Computer 2023 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.titleInvestigating Cognitive Load in Emergency Control Room Simulationsde
dc.typeText/Workshop Paper
gi.conference.date3.-6. September 2023
gi.conference.locationRapperswil
gi.conference.sessiontitleMCI-WS01: 10. Workshop Mensch-Maschine-Interaktion in sicherheitskritischen Systemen

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