Context Aware Data Gathering Study
NCT04154904 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 30
Last updated 2023-08-01
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.
Conditions
Interventions
- OTHER
-
Exercise
Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home.
Sponsors & Collaborators
-
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
collaborator NIH -
Oregon Health and Science University
lead OTHER
Principal Investigators
-
Jessica Castle, MD · Oregon Health and Science University
Study Design
- Allocation
- RANDOMIZED
- Purpose
- BASIC_SCIENCE
- Masking
- NONE
- Model
- PARALLEL
Eligibility
- Min Age
- 18 Years
- Max Age
- 65 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2020-08-11
- Primary Completion
- 2021-12-23
- Completion
- 2022-01-03
Countries
- United States
Study Locations
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