At a glance
ClinicalIndex Comparison RecordStandardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
Development of a Context-aware Glucose Prediction Algorithm in Patients With Type 1 Diabetes
In Brief
A clinical study evaluating Exercise for Type 1 Diabetes. Completed, enrolled 30 participants across 1 site.
Detailed Summary
Automated Insulin Delivery (AID) systems have now become an important standard-of-care for people with T1D and have demonstrated a reduction, but not elimination, of hypoglycemia during long-term studies. One limitation of current AID systems is that they have no knowledge about the context or environment that a person is currently experiencing. Contextual patterns can potentially improve the performance of an AID by recognizing environments or patterns of living that are related to changes in glucose. The team at OHSU is developing a context-aware glucose prediction algorithm that will capture context data from the patient both indoors and outdoors. This context data will be provided to the algorithm to allow for detecting contextual patterns that might relate to high or low glucose. The goal of this study will be the creation of a data set that will include contextual patterns along with glucose, insulin and physiological data.
Study Details
Timeline
Interventions
Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home.