SEMINAR: Biomechanical modeling to identify targets for improving ambulatory function


SEMINAR: Biomechanical modeling to identify targets for improving ambulatory function

Meeting ID: 973 7903 9358 Passcode: MAE

Jessica Allen, Ph.D.
Assistant Professor
Dept. of Chemical and Biomedical Engineering
West Virginia University
Neuromechanics of Mobility Lab

Restoration of ambulatory function is a high priority for rehabilitation interventions in pathological patients. Current interventions tend to follow a “one size fits all” approach that produce only modest improvements in ambulatory function. The prescription of personalized interventions is currently limited by our ability to characterize the individual-specific biomechanical impairments causing one’s poor ambulatory function. My work aims to model how various biomechanical impairments caused by aging, disease, and/or injury affect ambulatory function to help guide individualized clinical decision making. In this talk, I will highlight several examples of how I use both data-driven biomechanical models (i.e., machine learning) and first-principles biomechanical models (i.e., musculoskeletal simulations) to identify potential targets for the design and/or prescription of individualized interventions to improve ambulatory function.

Dr. Jessica Allen is an Assistant Professor in Biomedical Engineering at West Virginia University, where she directs the Neuromechanics of Mobility Lab. She received her B.S. in Mechanical Engineering from the University of Florida and her Ph.D. in Mechanical Engineering from the University of Texas at Austin. She then completed post-doctoral training at Emory University and Georgia Institute of Technology in the Department of Biomedical Engineering. During her training, she was a recipient of both an NSF graduate research fellowship and an NIH individual post-doctoral fellowship. Dr. Allen’s research group at WVU uses interdisciplinary techniques from engineering, machine learning, and biology to identify biomechanical targets that can guide interventional decisions for individuals with ambulatory impairments. This work is currently supported by grants from both NSF and NIH.


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