Abstract Details
Activity Number:
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243
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Imaging
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Abstract #313415
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View Presentation
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Title:
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A Quantitative Approach to the Diagnosis of Head Injuries Through a Spatio-Temporal Model of the Electrophysiological Assessment of Working Memory
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Author(s):
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Pavel Chernyavskiy*+ and Caitlin M. Hudac and Dennis L. Molfese and David B. Marx
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Companies:
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University of Nebraska-Lincoln and University of Nebraska-Lincoln and University of Nebraska-Lincoln and University of Nebraska
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Keywords:
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spatio-temporal ;
brain injuries ;
space-time ;
TBI ;
ERP
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Abstract:
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National awareness of traumatic brain injuries (TBI) is increasing given higher prevalence in both military and athletic settings. TBI affects both short-term and long-term brain and behavior mechanisms associated with cognitive deficits. Unfortunately, a quantitative approach to the identification and diagnosis of TBI has not yet been established. In this paper, authors use a spatio-temporal sum-metric model to represent electrophysiological assessments of working memory in college athletes. Athlete-specific parameter estimates are then used to evaluate two classification algorithms: Quadratic Discriminant Analysis and Nearest-k Neighbors in accurately predicting brain injuries. First, we demonstrate that a sum-metric model can be used to describe electrophysiological brain response in both temporal and spatial domains (i.e. across electrode locations). Second, we provide spatio-temporal profiles of injured and uninjured athletes. Finally, we show that both classifiers accurately predict head injuries using our estimated model parameters.
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Authors who are presenting talks have a * after their name.
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