Dr. Fadi Abdeljawad
Associate Professor
Department of Materials Science and Engineering
Lehigh University
Abstract
The integration of wearable technology and edge computing offers a transformative approach to manage the health and performance of individuals. The translation of wearable technology from commodity devices for weekend warriors to now companion digital therapeutics has heightened the utility and application across the technology readiness scale. Despite the increased adoption of wearable sensors, there remains a critical need to validate these technologies in large scale studies across diverse populations to assess their efficacy prior to their application for clinical decision-making purposes. In part one of this talk, the speaker will discuss on-going efforts to validate wearable technology for human performance applications and will summarize a technology validation framework utilized to assess the efficacy of such devices.
In part two of this talk, the speaker will focus on the development of machine learning models to forecast biomechanical and physiological metrics relevant to human performance using commercial off the shelf technology (COTS) devices. There has been a plethora of research focusing on professional athletes towards developing performance and injury risk stratification analytics however there lacks prospective, longitudinal studies for adolescents and collegiate athletics towards reducing injury burden. While we may have come out of the COVID-19 pandemic, the sports medicine field is currently going through a pandemic dealing with overuse injuries, which is plaguing youth athletes worldwide. There remains a critical need for objective data to complement subjective outcome measures to monitor workload profiles in the younger population to guide performance and rehabilitation plans. In the context of collegiate athletics, there lies significant disparities within each of the three divisions and within each division as well. This financial inequity is compounded between male and female sports, with male sports receiving considerable funding compared to the female cohorts. The speaker will highlight the use of wearable technology in collegiate athletics at Lehigh University in male and female sports including football and soccer. We discuss the integration of machine learning to translate data acquired from wearable technology from a reactive to proactive means for performance optimization and rehabilitation applications.
In part three of this talk, the speaker will describe foundational concepts in materials science, device physics and assembly processes for epidermal electronics, in 1D, 2D and 3D architectures. These set of devices introduce a soft, skin-mountable class of sensor system for this purpose with an emphasis on bio-inspired and bio-integrated technologies. The speaker will focus on the development of flexible epidermal electronic system for disease monitoring ranging from wound healing to neonatal vitals monitoring and to dysphagia. A key takeaway from this talk is the unique interdisciplinary and collaborative nature of the research between engineering and medicine to translate technologies to improve outcomes in the human performance domain.
About Fadi Abdeljawad
Dr. Fadi Abdeljawad is an Associate Professor in the Department of Materials Science and Engineering at Lehigh University. Prior to joining Lehigh in 2023, he was an Assistant-then-Associate Professor (2018-2023) at Clemson University. From 2014-2018, Dr. Abdeljawad was a Staff Scientist in the Computational Materials and Data Science Department at Sandia National Laboratories. He obtained his M.A. (2010) and Ph.D. (2014) from Princeton University. He is a recipient of the Army Research Office Young Investigator Program (YIP) Award; TMS Early Career Faculty Fellow Award; and Ralph E. Powe ORAU DOE Award. Abdeljawad’s research, which is funded by DOD, DOE, NSF, and U.S. National Laboratories, is focused on microstructure formation and evolution, interface physics, and mechanics. His work has been featured in journals such as Physical Review Letters, Nano Letters, Applied Physics Letters, and Nanoscale.