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.
This project seeks to identify the how walking impairments in stroke survivors contribute to mobility deficits through the use of behavioral observations and computational models. The chosen approach integrates biomechanical analyses, physiological assessments and machine learning algorithms to explain how asymmetries during walking influence balance and the effort required to walk. Ultimately, the results of this work may lead to more personalized rehabilitation strategies to improve walking capacity and efficiency, and ultimately reduce fall risk in stroke survivors.
Toward a Mechanistic Understanding of Optimization Principles Underlying Hemiparetic Gait
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: University of Southern California
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.