Abstract
This paper introduces a novel gait parameterization method that models gait kinematics as a continuous function of gait cycle phase, walking speed, and ground slope. Kinematic data was recorded from seven able-bodied subjects walking on a treadmill at twenty-seven combinations of walking speed and ground slope. Convex optimization was used to determine the parameters of a function of three variables that fits this experimental data. This function may be able to provide desired trajectories to a virtual constraint controller over a continuum of gait phases and ambulation modes. This could allow for a single, non-switching controller to control a prosthetic leg for a variety of tasks, avoiding many of the problems associated with the ubiquitous use of finite state machines in prosthesis control.
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