This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
Robotic lower limb exoskeletons aim to improve or augment limb functions. Automatic modulation of robotic assistance is very important because it can increase the assistive outcomes and guarantee safety when using exoskeletons. However, this automatic assistance adjustment is challenging due to person-to-person and day-to-day variations, as well as the time-varying complex human-machine-interaction forces. In recent years, human-in-the-loop optimization methods have been investigated to reduce participants' metabolic costs by providing personalized assistance from robotic exoskeletons. However, metabolic cost measure is noisy and the experimental protocol is usually relatively long. In addition, the influence of exoskeleton control on this human state in terms of energetic cost is unclear and indirect. More importantly, the optimization by reducing metabolic cost is found to affect human gait patterns and cause undesired outcomes. In this study, new evaluation measures other than metabolic cost will be investigated to optimize the assistance from a powered hip exoskeleton based on a reinforcement learning method. It is hypothesized that the new reinforcement learning-based optimal control approach will produce personalized torque assistance, reduce human volitional effort, and improve balance and other performance during walking tasks. Both participants without and with neurological disorders will be included in this study.
Learning-based Control of a Hip Exoskeleton to Improve Balance and Energetics of Human Walking Functions
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: North Carolina State University
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.