AN INITIAL EVALUATION OF IBI VIZEDIT: AN RSHINY APPLICATION FOR OBTAINING ACCURATE ESTIMATES OF AUTONOMIC REGULATION OF CARDIAC ACTIVITY

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dc.contributor.advisorRubin, Kenneth Hen_US
dc.contributor.authorBarstead, Matthewen_US
dc.contributor.departmentHuman Developmenten_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2019-02-08T06:32:09Z
dc.date.available2019-02-08T06:32:09Z
dc.date.issued2018en_US
dc.description.abstractPhotoplethysmogram (PPG) sensors are increasingly used to collect individual heart rate data during laboratory assessments and psychological experiments. PPG sensors are relatively cheap, easy to use, and non-invasive alternatives to the more common electrodes used to produce electrocardiogram recordings. The downside is that these sensors are more susceptible to signal distortion. Often, the most relevant measures for understanding psychological processes that underlie emotions and behaviors are measures of heart rate variability. As with all measures of variability, outliers (i.e., signal artifacts) can have outsized effects on the final estimates; and, given that these scores represent a primary variable of interest in many research contexts, the successful elimination of artefactual points is critical to the ability to make valid inferences with the data. Prior to the development of IBI VizEdit, there was no single, integrated processing and editing pipeline for PPG data. The present pair of studies offers and initial evaluation of the program’s performance. Study 1 is focused on the efficacy of a novel approach to imputing sections of particularly corrupted PPG signal. Study 2 tests the ability of trained editors to reliably use IBI VizEdit as well as the validity of estimates of cardiac activity during a prescribed set of laboratory tasks. Study 1 suggests that the novel imputation approach, under certain conditions and using certain parameterizations may hold promise as a means of accurately imputing missing sections of data. However, Study 1 also clearly demonstrates the need for further refinement and the consideration of alternative implementations. The results from Study 2 indicate that IBI VizEdit can be reliably used by trained editors and that estimates of cardiac activity derived from its output are likely valid.en_US
dc.identifierhttps://doi.org/10.13016/edq9-xmiq
dc.identifier.urihttp://hdl.handle.net/1903/21745
dc.language.isoenen_US
dc.subject.pqcontrolledPsychobiologyen_US
dc.subject.pqcontrolledQuantitative psychologyen_US
dc.subject.pquncontrolledBehavioral inhibitionen_US
dc.subject.pquncontrolledHeart Rate Variabilityen_US
dc.subject.pquncontrolledOpen-source methodsen_US
dc.subject.pquncontrolledPsychophysiologyen_US
dc.subject.pquncontrolledRespiratory Sinus Arrhythmiaen_US
dc.subject.pquncontrolledRShinyen_US
dc.titleAN INITIAL EVALUATION OF IBI VIZEDIT: AN RSHINY APPLICATION FOR OBTAINING ACCURATE ESTIMATES OF AUTONOMIC REGULATION OF CARDIAC ACTIVITYen_US
dc.typeDissertationen_US

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