BGEM Use as Blood Glucose Prediction Model in T2DM Population of Indonesia

Brief summary (registry, in English)

Using signals from consumer-grade PPG sensors on wrist wearables, smart rings or hearables, BGEM® AI model computes the relevant digital biomarkers correlated with the change of blood glucose level to predict a blood glucose result for monitoring and evaluating diabetic risks Ukrida in collaboration with Actxa \& Lif aims to enhance the current model's prediction accuracy to predict the blood glucose levels of individuals almost as accurately as a glucometer. To achieve this, Actxa aims to collect data from around 500 individuals with diabetes in this exercise and 400 healthy or undiagnosed (prediabetes/diabetes) individuals.

What you commit to

• Study type: Observational
• Participants enrolled: 885
• From 30 Jul 2024 to the primary completion date, 5 Oct 2024
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Age in the registry: 18 years to 59 years · Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (1)

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