Psychophysiological measures of mental effort and emotion within user research

dc.contributor.advisor Stephen Gilbert
dc.contributor.author Meusel, Chase
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.date 2018-08-11T06:06:01.000
dc.date.accessioned 2020-06-30T03:04:56Z
dc.date.available 2020-06-30T03:04:56Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2001-01-01
dc.date.issued 2017-01-01
dc.description.abstract <p>Psychophysiological measures have potential to aid the discipline of user research, but are currently under-utilized. Currently, across both academia and industry there is a need to increase the quality and quantity of feedback garnered from individuals during user tasks. Psychophysiological measures are beneficial in that they can collect data objectively, unobtrusively, and in real-time. The work put forth in this dissertation focuses on two separate contexts in which psychophysiological measures are used to increase the overall quality of user research data. The first context is described in Chapters 2 and 3, in which electrodermal activity (EDA) within a high fidelity combine simulator is used as a measure of mental effort. Due to both the natural complexity of operating a combine harvester and the relative lack of understanding of combine operators today, using psychophysiological measures within this environment serves to better understand the user without compromising the experience. The second context is described in Chapters 4 and 5, in which consumer level hardware is used to measure the emotional states of workplace employees. The hardware captured electrodermal activity and heart rate data from participants while they also submitted their emotional states as training data. These data were used to build a general emotion detection model which was then tested in real-time over the course of four weeks. Additionally, emotion reporting is explored through the lens of personality and models were built and evaluated to determine what, if any influence personality plays in emotional self-report. Both mental effort within the combine simulator and emotion detection using everyday technology seek to improve the overall understanding of the user and support the use of psychophysiological measures within user research.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/15577/
dc.identifier.articleid 6584
dc.identifier.contextkey 11058063
dc.identifier.doi https://doi.org/10.31274/etd-180810-5194
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/15577
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/29760
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/15577/Meusel_iastate_0097E_16685.pdf|||Fri Jan 14 20:43:12 UTC 2022
dc.subject.disciplines Behavioral Neurobiology
dc.subject.disciplines Behavior and Behavior Mechanisms
dc.subject.disciplines Biological Psychology
dc.subject.disciplines Databases and Information Systems
dc.subject.disciplines Other Psychology
dc.subject.disciplines Psychology
dc.subject.keywords Emotion
dc.subject.keywords Human Computer Interaction
dc.subject.keywords Human Factors
dc.subject.keywords Mental Effort
dc.subject.keywords Personality
dc.subject.keywords Psychophysiology
dc.title Psychophysiological measures of mental effort and emotion within user research
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
thesis.degree.discipline Human Computer Interaction
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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