Doctoral Dissertations
Date of Award
12-2020
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Biomedical Engineering
Major Professor
Jeffrey A. Reinbolt
Committee Members
Daniel C. Rucker, Eric Espinoza-Wade, Cyril J. Donnelly
Abstract
Most biological systems employ multiple redundant actuators, which is a complicated problem of controls and analysis. Unless assumptions about how the brain and body work together, and assumptions about how the body prioritizes tasks are applied, it is not possible to find the actuator controls. The purpose of this research is to develop computational tools for the analysis of arbitrary musculoskeletal models that employ redundant actuators. Instead of relying primarily on optimization frameworks and numerical methods or task prioritization schemes used typically in biomechanics to find a singular solution for actuator controls, tools for feasible sets analysis are instead developed to find the bounds of possible actuator controls. Previously in the literature, feasible sets analysis has been used in order analyze models assuming static poses. Here, tools that explore the feasible sets of actuator controls over the course of a dynamic task are developed. The cost-function agnostic methods of analysis developed in this work run parallel and in concert with other methods of analysis such as principle components analysis, muscle synergies theory and task prioritization. Researchers and healthcare professionals can gain greater insights into decision making during behavioral tasks by layering these other tools on top of feasible sets analysis.
Recommended Citation
Sundararajan, Aravind, "Dynamic Neuromechanical Sets for Locomotion. " PhD diss., University of Tennessee, 2020.
https://trace.tennessee.edu/utk_graddiss/6093
Included in
Applied Mechanics Commons, Biomechanical Engineering Commons, Dynamical Systems Commons, Engineering Physics Commons, Geometry and Topology Commons, Probability Commons