Learning to move in novel situations is a complex process. We need to continually learn the changing situations and determine the best way to move. Optimization is a widely accepted framework for this process. However, little is known about algorithms used by the nervous system to perform this optimization. Our lab recently found evidence that people can continuously optimize energy during walking. My goal in this thesis is to identify principles of optimization, particularly energy optimization in walking, that govern our choice of movement in novel situations. I used two novel walking tasks for this purpose. For the first task, I designed, built, and tested a mechatronic system that can quickly, accurately, and precisely apply forces to a user’s torso. It changes the relationship between a walking gait and its associated energetic cost—cost landscape—to shift the energy optimal walking gait. Participants shift their gait towards the new optimum in these landscapes. In my second project, I aimed to understand how the nervous system identifies when to initiate optimization. I used my system to create cost landscapes of three different cost gradients. I found that experiencing a steeper cost gradient through natural variability is not sufficient to cue the nervous system to initiate optimization. For my third and fourth projects, I used the task of split-belt walking. I collaborated with another research group to analyse the mechanics and energetics of walking with different step lengths on a split-belt treadmill. I found that people can harness energy from a split-belt treadmill by placing their leading leg further forward on the fast belt, and that there may be an energy optimal gait. In my fourth project, I used computer modelling to identify that there may exist an energy optimal gait due to the trade-off between the cost of swinging the leg and the cost of redirecting the body center of mass when transitioning from step to step. Together, these projects develop a new system and a new approach to understand energy optimization in walking. They uncover principles governing the initiation of this process and our ability to benefit from it.
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Thesis advisor: Donelan, Max
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