Keywords

Augmented Cognition, Physiological Measurement, Human Computer Interaction

Abstract

The purpose of this study is to determine under what conditions multiple minimally intrusive physiological sensors can be used together and validly applied for use in areas which rely on adaptive systems including adaptive automation and augmented cognition. Specifically, this dissertation investigated the physiological transitions of operator state caused by changes in the level of taskload. Three questions were evaluated including (1) Do differences exist between physiological indicators when examined between levels of difficulty? (2) Are differences of physiological indicators (which may exist) between difficulty levels affected by spatial ability? (3) Which physiological indicators (if any) account for variation in performance on a spatial task with varying difficulty levels? The Modular Cognitive State Gauge model was presented and used to determine which basic physiological sensors (EEG, ECG, EDR and eye-tracking) could validly assess changes in the utilization of two-dimensional spatial resources required to perform a spatial ability dependent task. Thirty-six volunteers (20 female, 16 male) wore minimally invasive physiological sensing devices while executing a challenging computer based puzzle task. Specifically, participants were tested with two measures of spatial ability, received training, a practice session, an experimental trial and completed a subjective workload survey. The results of this experiment confirmed that participants with low spatial ability reported higher subjective workload and performed poorer when compared to those with high spatial ability. Additionally, there were significant changes for a majority of the physiological indicators between two difficulty levels and most importantly three measures (EEG, ECG and eye-tracking) were shown to account for variability in performance on the spatial task.

Notes

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Graduation Date

2009

Advisor

Nicholson, Denise

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Degree Program

Modeling and Simulation

Format

application/pdf

Identifier

CFE0002781

URL

http://purl.fcla.edu/fcla/etd/CFE0002781

Language

English

Release Date

September 2009

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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