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dc.contributor.advisorFerris, Thomas K.
dc.contributor.advisorSasangohar, Farzan
dc.creatorRodriguez Paras, Carolina
dc.date.accessioned2022-01-27T22:20:16Z
dc.date.available2023-08-01T06:42:01Z
dc.date.created2021-08
dc.date.issued2021-08-06
dc.date.submittedAugust 2021
dc.identifier.urihttps://hdl.handle.net/1969.1/195428
dc.description.abstractHigh cognitive workload in multitasking, safety-critical environments can lead to performance degradation, resulting in increased safety risks or errors. The problem arises when the person reaches the redline of cognitive workload, which occurs when the task demands exceed the available cognitive resources necessary to continue performing the tasks at an adequate performance level. While the redline is different for every person, an ability to understand how to detect the threshold can provide input for strategies in mental resource allocation to prevent performance degradation. Historically, the redline of cognitive workload has been measured using subjective and performance measures. Subjective measures provide insight into the human’s perceived mental workload level, and may be collected concurrently with the task, but this may require additional cognitive resources. When subjective measures are collected after the task, memory decay may occur. Performance is usually observed after the task, and when workload reaches a certain level, any additional increases in cognitive workload can lead to degraded performance. Physiological measures have also been used to measure cognitive workload, but physiological patterns have yet to be investigated as indicators of the redline of cognitive workload. Physiological measures, such as heart rate, heart rate variability, and skin conductance reflect changes occurring in both branches of the autonomic nervous system: the sympathetic and parasympathetic. They can be collected in real-time through unobtrusive, wearable devices. The current research aims to gather a better understanding of how high levels of cognitive workload are reflected in physiological measures, and can be used to infer when the person is approaching their redline of cognitive workload. This research contributes to the body of knowledge by providing a better understanding of the redline of cognitive workload, which can be detected based physiological patterns. The complex relationship between both branches of the autonomic nervous system (sympathetic and parasympathetic) were explored, and used to investigate when the person may be approaching their redline of cognitive workload.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectCognitive redlineen
dc.subjectperformance redlinesen
dc.subjectcognitive workloaden
dc.subjectphysiological measuresen
dc.subjectautonomic indices of cognitive workloaden
dc.titlePhysiological Indicators of Cognitive Workload as Detectors of Performance Redlinesen
dc.typeThesisen
thesis.degree.departmentIndustrial and Systems Engineeringen
thesis.degree.disciplineIndustrial Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberCurrie-Gregg, Nancy J.
dc.contributor.committeeMemberTassinary , Louis G.
dc.type.materialtexten
dc.date.updated2022-01-27T22:20:16Z
local.embargo.terms2023-08-01
local.etdauthor.orcid0000-0003-1330-9202


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