Las Vegas, Nevada
April 18, 2024
April 18, 2024
April 20, 2024
11
10.18260/1-2--46021
https://peer.asee.org/46021
91
Dr. Christine King is an Associate Teaching Professor of Biomedical Engineering at UC Irvine. She received her BS and MS from Manhattan College in Mechanical Engineering and her PhD in Biomedical Engineering from UC Irvine, where she developed brain-computer interface systems for neurorehabilitation. She was a post-doctorate in the Wireless Health Institute at the University of California, Los Angeles, and a research manager in the Center for SMART Health, where she focused on wireless health monitoring for stroke and pediatric asthma. Her current research is on engineering education and women's health, specializing in pedagogy strategies to promote learning and innovation in design-build-test courses, including senior design, computer programming, and computer-aided-design courses, as well as pre-partum and partum medical devices.
Matthew Lo is a graduate student pursuing his Master of Engineering in Biomedical Engineering at UC Irvine. He completed his BS in Biomedical Engineering: Premedical from UC Irvine, during which he lead and participated in a wide range of research, including (1) refining virtual reality modalities to improve medical training, (2) analyzing the mechanisms of slip and maintaining balance, (3) characterizing neuronal endolysosomal vesicle stages in Alzheimer’s Disease, (4) developing a spectroscopy device to age bruises primarily for domestic abuse, (5) designing an angioplasty balloon catheter to increase the accuracy of stenting, and 6) creating a treatment device for paravalvular leak. Currently, Matthew continues most of his research from his undergraduate career, and is developing a contactless device for measuring vitals for his Master’s capstone. Although mainly focused on medical device research and development, as an aspiring physician-scientist, Matthew has a deep commitment to advancing medical education to ultimately improve both patient care and outcomes through his research to better understand physiological correlations with attention and to create novel and engaging virtual clinical experiences.
Milan Das is an undergraduate student pursuing his Bachelor of Science in Biomedical Engineering at UC Irvine, along with a Minor in Information and Computer Science. In his research work, Milan has developed extensive code to properly quantify electroencephalogram (EEG) and eye-tracking data underlying boredom and engagement in students for the identification of unmet clinical needs. With a passion for interdisciplinary innovation at the intersection of biomedical engineering and computer science, Milan has dedicated his undergraduate career to exploring new frontiers in medical technology. Spearheading projects in artificial intelligence for healthcare, Milan showcases his expertise in developing cutting-edge solutions to address public unmet needs. Currently, he is focused on prototyping a smart insole that utilizes machine learning to analyze gait and detect potential abnormalities that may require medical intervention.
Dalton Salvo is a doctoral candidate in the Dept. of English at UC Irvine. He received his BA from the Univ. of San Diego, a MS in English Literature from the Univ. of Edinburgh, a MA in Rhetoric and Writing Studies from San Diego State Univ., and a MA in English literature from UC Irvine. His current research centers on identifying mental and emotional states generated through human interaction with virtual reality and other virtual artifacts by analyzing physiological data and applying that research to create more effective virtual learning environments. Leveraging this work, he is currently creating a persistent and interactive virtual environment for hosting remote learning classes in the Dept. of Biomedical Engineering at UC Irvine.
Full Paper Submission:
Biomedical engineers can enhance their capacity for innovation by cultivating critical skills in identifying unmet clinical needs through clinical immersion. However, limited access to medical spaces and growing class sizes hinder their ability to experience in-person immersion. In response, we have developed a virtual reality (VR) clinical immersion platform for students to explore unmet clinical needs. Through analysis of eye gaze behavior, this study aimed to unveil whether engagement can be assessed within the VR clinical environment. Using a VR headset with eye tracking, we assessed participants within three selected environments: an exciting, boring, and clinically immersive operating room. Intentionally designed to elicit responses from boredom to engagement, these videos were used to identify potential physiological features. The results indicated that there are distinct patterns in pupil dilation and eye gaze deviation. The boring video elicited the greatest eye gaze deviation from center variance, signifying heightened disengagement, whereas the exciting conspiracy video demonstrated minimal deviation, indicating sustained attention. In comparison, the clinical immersion video had eye gaze patterns closer to the engagement video, as the data was significantly different from the boring video (p = 0.0004, N = 12). Given these results, the ability to perform eye tracking was assessed through webcams to determine if this feature can be utilized in online courses via laptops. The webcams had a high level of accuracy (0.874 ± 0.027, N = 4), indicating that eye gaze can potentially be used to gauge engagement within VR environments for just-in-time learning interventions.
King, C. E., & Lo, M., & Das, M., & Salvo, D. (2024, April), Assessment of Student Engagement in Virtual Reality Clinical Immersion Environments through Eye Tracking Paper presented at 2024 ASEE PSW Conference, Las Vegas, Nevada. 10.18260/1-2--46021
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