Continuous glucose monitoring systems-Current status and future perspectives of the flagship technologies in biosensor research

I Lee, D Probst, D Klonoff, K Sode - Biosensors and Bioelectronics, 2021 - Elsevier
Diabetes mellitus is a chronic illness in the United States affecting nearly 120 million adults,
as well as increasing in children under the age of 18. Diabetes was also the 7th leading …

Physical activity and psychological stress detection and assessment of their effects on glucose concentration predictions in diabetes management

M Sevil, M Rashid, I Hajizadeh, M Park… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Objective: Continuous glucose monitoring (CGM) enables prediction of the future glucose
concentration (GC) trajectory for making informed diabetes management decisions. The …

Identifiability of control-oriented glucose-insulin linear models: review and analysis

JD Hoyos, MF Villa-Tamayo, CE Builes-Montaño… - IEEE …, 2021 - ieeexplore.ieee.org
One of the main challenges of glucose control in patients with type 1 diabetes is identifying a
control-oriented model that reliably predicts the behavior of glycemia. Here, a review is …

Plasma-insulin-cognizant adaptive model predictive control for artificial pancreas systems

I Hajizadeh, M Rashid, A Cinar - Journal of process control, 2019 - Elsevier
An adaptive model predictive control (MPC) algorithm with dynamic adjustments of
constraints and objective function weights based on estimates of the plasma insulin …

Incorporating unannounced meals and exercise in adaptive learning of personalized models for multivariable artificial pancreas systems

I Hajizadeh, M Rashid, K Turksoy… - Journal of diabetes …, 2018 - journals.sagepub.com
Background: Despite the recent advancements in the modeling of glycemic dynamics for
type 1 diabetes mellitus, automatically considering unannounced meals and exercise …

Multivariable recursive subspace identification with application to artificial pancreas systems

I Hajizadeh, M Rashid, K Turksoy, S Samadi, J Feng… - IFAC-PapersOnLine, 2017 - Elsevier
Designing a fully automated artificial pancreas (AP) system is challenging. Changes in the
glucose-insulin dynamics in the human body over time, and the inter-subject and day-to-day …

Kalman smoothing for objective and automatic preprocessing of glucose data

OM Staal, S Sælid, A Fougner… - IEEE journal of …, 2018 - ieeexplore.ieee.org
A method for preprocessing a time series of glucose measurements based on Kalman
smoothing is presented. Given a glucose data time series that may be irregularly sampled …

An adaptive nonlinear basal-bolus calculator for patients with type 1 diabetes

D Boiroux, TB Aradóttir, K Nørgaard… - Journal of diabetes …, 2017 - journals.sagepub.com
Background: Bolus calculators help patients with type 1 diabetes to mitigate the effect of
meals on their blood glucose by administering a large amount of insulin at mealtime …

Estimation of process noise variances from the measured output sequence with application to the empirical model of type 1 diabetes

M Dodek, E Miklovičová - Biomedical Signal Processing and Control, 2023 - Elsevier
This paper presents a novel method for estimating a priori unknown variances of the process
noise affecting a general discrete-time stochastic state-space model under the assumption …

Nonlinear model predictive control and artificial pancreas technologies

D Boiroux, JB Jørgensen - 2018 ieee conference on decision …, 2018 - ieeexplore.ieee.org
A single-hormone artificial pancreas (AP) for people with type 1 diabetes consists of a
continuous glucose monitor (CGM), a control algorithm, and an insulin pump for …