제 1형 당뇨병을 위한 디지털 트위: 개인 맞춤형 글루코스-인슐린 수학 모델 개발

Abstract

This study introduces a Digital Twin Model (DTM) for Type 1 Diabetes Mellitus (T1DM), tailored to reduce the data needed for effective glucose management. We developed a personalized model using a simplified Bergman minimal model, focusing on individualized parameters that reflect physiological characteristics like glucose sensitivity and metabolism rates. Verification was conducted using data from Yorkshire pigs due to their similar glucose response to humans, demonstrating high correlation between the DTM predictions and actual data. This approach significantly shortens the data acquisition process and reduces the complexity of traditional methods. The results indicate that our DTM can accurately simulate glucose levels based on minimal input, offering a promising tool for enhancing diabetes management and reducing patient burden. This research may serve as a foundation for developing new medical devices for T1DM management.