A review of IoT systems to enable independence for the elderly and disabled individuals

AJ Perez, F Siddiqui, S Zeadally, D Lane - Internet of Things, 2023 - Elsevier
Recent years have witnessed an increase in human life expectancy fueled by significant
improvements in infrastructure, healthcare, and economies across the globe. Longer life …

Management of type 1 diabetes in pregnancy: update on lifestyle, pharmacological treatment, and novel technologies for achieving glycaemic targets

K Benhalima, K Beunen, SE Siegelaar… - The Lancet Diabetes & …, 2023 - thelancet.com
Glucose concentrations within target, appropriate gestational weight gain, adequate lifestyle,
and, if necessary, antihypertensive treatment and low-dose aspirin reduces the risk of pre …

Recent development of drug delivery systems through microfluidics: From synthesis to evaluation

Z Ma, B Li, J Peng, D Gao - Pharmaceutics, 2022 - mdpi.com
Conventional drug administration usually faces the problems of degradation and rapid
excretion when crossing many biological barriers, leading to only a small amount of drugs …

Basal Glucose Control in Type 1 Diabetes Using Deep Reinforcement Learning: An In Silico Validation

T Zhu, K Li, P Herrero… - IEEE Journal of Biomedical …, 2020 - ieeexplore.ieee.org
People with Type 1 diabetes (T1D) require regular exogenous infusion of insulin to maintain
their blood glucose concentration in a therapeutically adequate target range. Although the …

[HTML][HTML] Experiences of young people and their caregivers of using technology to manage type 1 diabetes mellitus: systematic literature review and narrative synthesis

N Brew-Sam, M Chhabra, A Parkinson, K Hannan… - JMIR …, 2021 - diabetes.jmir.org
Background: In the last decade, diabetes management has begun to transition to technology-
based care, with young people being the focus of many technological advances. Yet …

An insulin bolus advisor for type 1 diabetes using deep reinforcement learning

T Zhu, K Li, L Kuang, P Herrero, P Georgiou - Sensors, 2020 - mdpi.com
(1) Background: People living with type 1 diabetes (T1D) require self-management to
maintain blood glucose (BG) levels in a therapeutic range through the delivery of exogenous …

Automated insulin delivery for pregnant women with type 1 diabetes: where do we stand?

K Benhalima, J Jendle, K Beunen… - Journal of diabetes …, 2024 - journals.sagepub.com
Automated insulin delivery (AID) systems mimic an artificial pancreas via a predictive
algorithm integrated with continuous glucose monitoring (CGM) and an insulin pump …

Randomized controlled trial of mobile closed-loop control

B Kovatchev, SM Anderson, D Raghinaru… - Diabetes …, 2020 - Am Diabetes Assoc
OBJECTIVE Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system.
RESEARCH DESIGN AND METHODS This protocol, NCT02985866, is a 3-month parallel …

Outpatient randomized crossover comparison of zone model predictive control automated insulin delivery with weekly data driven adaptation versus sensor …

JE Pinsker, E Dassau, S Deshpande… - Diabetes technology …, 2022 - liebertpub.com
Background: Automated insulin delivery (AID) systems have proven effective in increasing
time-in-range during both clinical trials and real-world use. Further improvements in …

[HTML][HTML] Review of automated insulin delivery systems for individuals with type 1 diabetes: tailored solutions for subpopulations

EM Aiello, S Deshpande, B Özaslan… - Current opinion in …, 2021 - Elsevier
Automated insulin delivery (AID) systems have proven safe and effective in improving
glycemic outcomes in individuals with type 1 diabetes (T1D). Clinical evaluation of this …