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.
The goal of this observational study is to learn about the usefulness of automated analysis of speech, physical activity measures tracked using wearable devices at home, and tremor detection measured using computer-vision analysis of smartphone video to detect impairments related to Parkinson's disease and improve prediction of one-year progression. Participants will attend a short research visit at the University of Iowa. During this visit, they will make a video recording using a smartphone of them performing a fine motor task and audio recordings of pre-written text. They will be provided with an activity tracker and asked to wear it at home for four weeks. After four weeks, a video visit will be conducted and the speech and video tasks will be repeated.
Remote Monitoring Using Commercially Available Activity Trackers and Computer Vision Provides a Holistic, Low-cost Assessment of Parkinson's Disease Symptoms
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: Jacob E. Simmering
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.