[HTML][HTML] Non-invasive glucose sensing technologies and products: a comprehensive review for researchers and clinicians

D Di Filippo, FN Sunstrum, JU Khan, AW Welsh - Sensors, 2023 - mdpi.com
Diabetes Mellitus incidence and its negative outcomes have dramatically increased
worldwide and are expected to further increase in the future due to a combination of …

Forecasting glycaemia for type 1 diabetes mellitus patients by means of IoMT devices

I Rodríguez-Rodríguez, M Campo-Valera… - Internet of Things, 2023 - Elsevier
The chronic metabolic condition, Type 1 diabetes mellitus (DM1), is marked by consistent
hyperglycemia due to the body's inability to produce sufficient insulin. This necessitates the …

[HTML][HTML] Multimodal in-vehicle hypoglycemia warning for drivers with type 1 diabetes: design and evaluation in simulated and real-world driving

C Bérubé, M Maritsch, VF Lehmann… - JMIR human …, 2024 - humanfactors.jmir.org
Background: Hypoglycemia threatens cognitive function and driving safety. Previous
research investigated in-vehicle voice assistants as hypoglycemia warnings. However, they …

Enhancing Wearable based Real-Time Glucose Monitoring via Phasic Image Representation Learning based Deep Learning

Y Zhu, NB Aimandi, MAU Alam - arXiv preprint arXiv:2406.16926, 2024 - arxiv.org
In the US, over a third of adults are pre-diabetic, with 80\% unaware of their status. This
underlines the need for better glucose monitoring to prevent type 2 diabetes and related …

Transform Diabetes-Harnessing Transformer-Based Machine Learning and Layered Ensemble with Enhanced Training for Improved Glucose Prediction.

RA Laursen, P Alo - 2023 - uia.brage.unit.no
Type 1 diabetes is a common chronic disease characterized by the body's inability to
regulate the blood glucose level, leading to severe health consequences if not handled …

Prediction of Interstitial Glucose Levels Through Wearable Sensors Using Machine Learning

H Ali, S Madanian, N Malik, D White… - 2023 IEEE Asia …, 2023 - ieeexplore.ieee.org
The incidence of diabetes has been increasing, resulting in an increasing cost of managing
and tracking the correlates for blood glucose levels. Just for New Zealand alone, 2.1 billion …

Enhancing Elderly Care: Remote Glucose Monitoring for Health and Independence

A Mehrotra, P Ashok, S Sudheer… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
This paper presents a comprehensive approach to non-invasive glucose monitoring for
elderly diabetic patients by integrating machine learning algorithms, loT devices, and cloud …

Improving Blood Glucose Prediction for People with T1DM During Physical Activity Using Machine Learning on Participant Collected Data

D Oh - 2024 - munin.uit.no
For people with Type 1 Diabetes Mellitus (T1DM), engaging in physical activities (PA)
presents unique challenges. The aim of this thesis was to improve the prediction of blood …

Blood Glucose Monitoring Using Non-Invasive Features of Wearable Devices and Machine Learning

J Zhang, X Huang, Q Chen - Proceedings of the 2024 3rd Asia …, 2024 - dl.acm.org
With the increasing number of people with diabetes and the popularity of wearable devices,
it becomes a novel research direction to use sensor data from wearable devices to monitor …

Synthetic health data generation for enhancement of non-invasive diabetes AI-based prediction

WAC Castañeda, P Bertemes Filho - 2023 - preprints.org
Continuous glucose monitoring devices allow diabetes condition management. However,
when limited data is available, one option is to increase their size by generating synthetic …