Publication Date

2021

Document Type

Dissertation

Committee Members

Thomas Wischgoll, Ph.D. (Advisor); Yong Pei, Ph.D. (Committee Member); Michael Raymer, Ph.D. (Committee Member); Sharon Farra, Ph.D. (Committee Member)

Degree Name

Doctor of Philosophy (PhD)

Abstract

Human errors in healthcare can be fatal. Proper physical assessment of patients to avoid such errors is of paramount importance. Incorrect or insufficient assessment of the patient can cause treatment delays that may lead to negative outcomes. In this dissertation we introduce innovative technology to assist surgeons in patient assessment as well as during the training of nurses in order to enhance learning. Technological advancements have made it possible to visualize overlays of computer-generated 3D models on real-world surfaces. This technology is called augmented reality. Using Steady State Topography (SST) brain imaging to examine the brain activity of people who participated in AR and non-AR tasks, Heather Andrew et. al. [13] demonstrated that visual attention is almost doubled when performing AR tasks when compared to non-AR tasks. Memory retention is also demonstrated to be 70% higher for AR experiences. Other studies show that the long-term memory of the learner can be enhanced by using multiple media interactions in the learning process [12]. The ability to project images accurately placed onto real-world physical objects using headsets could lead to increased retention of precision performance related to techniques in the physical assessment of the patient. This particular study deals with using AR to help surgeons visualize and assess the internal organs of a patient, particularly the rib cage. This study also proposes the use of using a similar variation of the application to enable nursing students to learn the necessary physical techniques required during the assessment of the heart and the lungs. Students will be able to visualize an overlay of the ribs, heart, and lungs to increase understanding of the accurate placement of devices required for assessing cardiac and respiratory issues using anatomical landmarks.

Page Count

85

Department or Program

Department of Computer Science and Engineering

Year Degree Awarded

2021


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