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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Taylor Dick, Ph.D.
School of Biomedical Sciences, University of Queensland, Australia
Department of Mechanical Engineering, Georgia Tech
Abstract
Skeletal muscle is the engine that produces force to power movement in humans and animals alike. To date the invasive nature of obtaining muscle-tendon forces in humans has limited our understanding of muscle function and restricted our ability to develop effective treatment protocols for diseased populations. Phenomenological, Hill-type models of the muscle are often used to predict muscle force, for example within musculoskeletal simulations of human movement. However, few studies have examined the accuracy of forces obtained from such models during in vivo motor tasks. The goal of my work is to develop, test, and refine methods to better quantify muscle mechanical output in humans, using ultrasound and electromyographic recordings, together with advanced Hill-type models. In this seminar I will first discuss imaging techniques to non-invasively estimate in vivo muscle-tendon forces. Next, I will present a series of comparisons between ultrasound-based force estimates and predictions from traditional Hill-type models as well as from new-age models that account for task-dependent changes in motor unit recruitment or alterations in 3-dimensional muscle shape. These studies are helping to identify the contractile and architectural features of muscle models that are most critical for predicting time-varying patterns of force during dynamic muscle contractions in healthy and clinical populations. Finally, I will share new insights into how we are using ultrasound imaging to look ‘under the skin’ during tasks where muscle-tendon behaviour is challenging to predict—for example, during exoskeleton-assisted walking or during recovery from a fall.
