S
Sediqeh Samadi
Researcher at Illinois Institute of Technology
Publications - 32
Citations - 783
Sediqeh Samadi is an academic researcher from Illinois Institute of Technology. The author has contributed to research in topics: Artificial pancreas & Control theory. The author has an hindex of 14, co-authored 31 publications receiving 538 citations.
Papers
More filters
Journal ArticleDOI
Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System
TL;DR: A novel meal-detection algorithm based on continuous glucose measurements that is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements is developed.
Journal ArticleDOI
Meal Detection and Carbohydrate Estimation Using Continuous Glucose Sensor Data
TL;DR: A meal detection and meal-size estimation algorithm is developed for use in artificial pancreas (AP) control systems for people with type 1 diabetes that detects the consumption of a meal and estimates its carbohydrate (CHO) amount to determine the appropriate dose of insulin bolus for a meal.
Journal ArticleDOI
Automatic Detection and Estimation of Unannounced Meals for Multivariable Artificial Pancreas System
Sediqeh Samadi,Mudassir Rashid,Kamuran Turksoy,Jianyuan Feng,Iman Hajizadeh,Nicole Hobbs,Caterina Lazaro,Mert Sevil,Elizabeth Littlejohn,Ali Cinar +9 more
TL;DR: A meal module is proposed to detect the consumption of a meal and to estimate the amount of carbohydrate (CHO) intake and integration of the meal module into a multivariable AP system allows revision of estimated CHO based on knowledge about physical activity, sleep, and the risk of hypoglycemia before the final decision for a meal bolus is made.
Journal ArticleDOI
Plasma Insulin Estimation in People with Type 1 Diabetes Mellitus
Iman Hajizadeh,Mudassir Rashid,Kamuran Turksoy,Sediqeh Samadi,Jianyuan Feng,Nicole Frantz,Mert Sevil,Eda Cengiz,Ali Cinar +8 more
TL;DR: In this paper, a real-time estimation of plasma insulin concentration (PIC) to quantify the insulin in the bloodstream in patients with type 1 diabetes mellitus (T1DM) is presented.
Journal ArticleDOI
Incorporating Unannounced Meals and Exercise in Adaptive Learning of Personalized Models for Multivariable Artificial Pancreas Systems.
Iman Hajizadeh,Mudassir Rashid,Kamuran Turksoy,Sediqeh Samadi,Jianyuan Feng,Mert Sevil,Nicole Hobbs,Caterina Lazaro,Zacharie Maloney,Elizabeth Littlejohn,Ali Cinar +10 more
TL;DR: An adaptive model identification technique that incorporates exercise information and estimates of the effects of unannounced meals obtained automatically without user input is proposed, able to identify reliable time-varying individualized glucose-insulin models.