Introduction In most everyday activities, we head towards a specific goal by updating our choices for a more direct path. For instance, when navigating toward a tall building, we can constantly update our road selection to get there. However, there are specific clinical tasks where taking the direct path is more challenging. Clinical investigations of optimizing a prosthesis involve the assessment of multiple parameter settings through trial and error rather than goal-directed optimization. Human-in-the-loop optimization algorithms allow devices to directly change in response to physiological changes (i.e., metabolic cost) of the user [1]. This methodology has proven very useful in advancing the optimization of robotic exoskeletons [2]. However, to our knowledge, this method has not yet been used for applications that involve manual alterations to a device. We investigate if a human-in-the-loop optimization algorithm can guide manual alterations to a prosthesis-simulating device to reduce the ground reaction force on the contralateral limb [3]. We hypothesized that the optimal parameter setting would reduce the loading rate on the contralateral limb compared to the initial tested parameter setting. If effective, this method could reduce the time taken for prosthetic fitting consultations.
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