Abstract

In lieu of real patients, healthcare educators frequently use simulated patients. Simulated patients can be realized in physical form, such as mannequins and trained human actors, or virtual form, such as via computer graphics presented on two-dimensional screens or head-mounted displays. Each of these alone has its strengths and weaknesses. I introduce a new class of physical-virtual patient (PVP) simulators that combine strengths of both forms by combining the flexibility and richness of virtual patients with tangible characteristics of a human-shaped physical form that can also exhibit a range of multi-sensory cues, including visual cues (e.g., capillary refill and facial expressions), auditory cues (e.g., verbal responses and heart sounds), and tactile cues (e.g., localized temperature and pulse). This novel combination of integrated capabilities can improve patient simulation outcomes. In my Ph.D. work I focus on three primary areas of related research. First, I describe the realization of the technology for PVPs and results from two user-studies to evaluate the importance of dynamic visuals and human-shaped physical form in terms of perception, behavior, cognition, emotions, and learning. Second, I present a general method to numerically evaluate the compatibility of any simulator-scenario pair in terms of importance and fidelity of cues. This method has the potential to make logistical, economic, and educational impacts on the choices of utilizing existing simulators. Finally, I describe a method for increasing human perception of simulated humans by exposing participants to the simulated human taking part in a short, engaging conversation prior to the simulation.

Notes

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Graduation Date

2019

Semester

Fall

Advisor

Welch, Gregory

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Degree Program

Modeling and Simulation

Format

application/pdf

Identifier

CFE0007750

URL

http://purl.fcla.edu/fcla/etd/CFE0007750

Language

English

Release Date

June 2024

Length of Campus-only Access

5 years

Access Status

Doctoral Dissertation (Campus-only Access)

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