Title: “Exploring the neuromechanical principles of artificially stabilized upright stance”
Thesis Supervisor: Dr. Mark Carpenter
Committee Members: Dr. Tim Inglis, Dr. Romeo Chua
Chair: Dr. Kayla Fewster
Abstract: Upright standing is inherently unstable but is stabilized by torque generated at the ankle joint. Standing behaviour can be simulated with a linear feedback control model, which assumes that ankle torque is generated in response to deviations of the body from equilibrium. However, contrary to assumptions of the feedback control model, a novel experimental paradigm revealed increases in ankle torque when the body is artificially stabilized. The aim of this thesis is to investigate the neuromechanical processes governing standing balance in an artificial stabilization paradigm using an integrative approach involving systematic sensorimotor manipulations and computational modelling. The first two studies of this thesis will examine whether positive torque feedback contributes to upright standing balance. Feedback control models incorporate a low-pass filtered positive torque feedback loop to simulate low-frequency dynamics of balance, but this mechanism has not been tested in upright human standing. Preliminary results from study 1 provide experimental evidence of a positive torque feedback mechanism, and study 2 aims to further explore the physiological systems underlying positive torque feedback. The remaining three studies of this thesis will use optimization and model-fitting procedures to identify a feedback control model of artificially stabilized balance and provide physiologically meaningful interpretations of experimental data. Study 3 will identify model parameters associated with low-frequency balance behaviour through a system identification approach. Study 4 will examine how the artificial stabilization paradigm interacts with the feedback control model through model-fitting and sensitivity analyses. Study 5 will implement the optimized model (developed across studies 1-4) in an examination of the influence of sway-relevant sensory information on behaviour in the artificial stabilization paradigm. This research will improve our understanding of the neural control of balance and will contribute important insights into the development of computational models of standing balance.