AIMC Topic: Blood Glucose Self-Monitoring

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Assessment of Blood Glucose Measurement Using New Noninvasive Technology: Protocol and Methodology.

JMIR research protocols
BACKGROUND: Diabetes mellitus (DM) is a major noncommunicable disease with a significant increase in prevalence, especially in low- and middle-income countries. The latest International Diabetes Federation Diabetes Atlas (2025) reports that 11.1% of ...

Intelligent glucose management in hospitalized patients: Short-term glucose and adverse events prediction.

PloS one
The management of blood glucose in hospitalized patients is confined to retrospective interventions, preventing healthcare professionals from predicting patients' blood glucose levels and potential adverse events in advance. This study employs a deep...

A multimodal physiological dataset for non-invasive blood glucose estimation.

Scientific data
Diabetes is a major health challenge that affects millions of people worldwide. Managing diabetes effectively requires monitoring blood glucose levels continuously, typically through invasive sensing devices such as continuous glucose monitors (CGMs)...

A personalized federated learning-based glucose prediction algorithm for high-risk glycemic excursion regions in type 1 diabetes.

Scientific reports
Continuous glucose monitoring (CGM) devices allow real-time glucose readings leading to improved glycemic control. However, glucose predictions in the lower (hypoglycemia) and higher (hyperglycemia) extremes, referred as glycemic excursions, remain c...

A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.

Scientific reports
The accurate prediction of blood glucose is critical for the effective management of diabetes. Modern continuous glucose monitoring (CGM) technology enables real-time acquisition of interstitial glucose concentrations, which can be calibrated against...

Predicting postprandial glucose excursions to personalize dietary interventions for type-2 diabetes management.

Scientific reports
Elevated postprandial glucose levels present a global epidemic and a major challenge in type-2 diabetes (T2D) management. A key barrier to developing effective dietary interventions for T2D management is the wide inter-individual variation in glycemi...

Detection of fasting blood sugar using a microwave sensor and convolutional neural network.

Scientific reports
Monitoring of fasting blood sugar (FBS) is a critical component in the diagnosis and management of diabetes, one of the most widespread chronic diseases globally. Microwave sensing-particularly through microstrip-based sensors-has recently gained att...

Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.

Journal of diabetes science and technology
BACKGROUND: Since the discovery of the life-saving hormone insulin in 1921 by Dr Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longe...

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

PloS one
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...