MedTrace Logo

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

NCT06642467 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 885

Last updated 2024-10-15

No results posted yet for this study

Summary

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.

Conditions

  • Diabete Type 2

Interventions

DEVICE

BGEM

BGEM is an ai driven model to predict blood glucose using ppg sensor

Sponsors & Collaborators

  • Actxa

    collaborator UNKNOWN

  • Lif

    collaborator UNKNOWN

  • Krida Wacana Christian University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
59 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-07-30
Primary Completion
2024-10-05
Completion
2024-10-05

Countries

  • Indonesia

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06642467 on ClinicalTrials.gov