Nicole Hobbs, United States of America

Illinois Institute of Technology Biomedical Engineering

Presenter Of 2 Presentations

MULTIVARIABLE SIMULATION SOFTWARE OF TYPE 1 DIABETES: A FREELY AVAILABLE RAPID-PROTOTYPING ENVIRONMENT FOR EXERCISE-ORIENTED ARTIFICIAL PANCREAS SYSTEMS

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:43 - 09:44

Abstract

Background and Aims

Interest in artificial pancreas (AP) systems has increased as hybrid-APs have become available for use in daily life. These first-generation systems require manual announcements of meals and exercise, causing management burden to users. Interest in use of additional signals such as heart rate or accelerometer signals to automate and improve AP performance during physical activities is growing. While T1D simulators which accurately model glucose-insulin dynamics exist, they do not provide physiological signals to allow for rapid-prototyping of multivariable AP systems. A multivariable simulator enables rapid advances in multivariable AP research.

Methods

The effect of exercise on glucose dynamics is combined with the Hovorka glucose-insulin dynamic model. Additional models compute physiological signals (heart rate, energy expenditure, and accelerometer values) with their dynamics driven by physical activity. Data for these signals was collected in clinical studies of people with T1D and are used to characterize the interpatient variability and determine realistic parameters for the virtual subjects.

Results

The root mean square error for the original Hovorka model (12.86±6.37mg/dL) is reduced (9.85±5.13mg/dL) when validated against 18 adults with T1D (p=6.4x10-7). This simulator (mGIPsim) is freely available for academic research. Users of mGIPsim provide the meal and exercise scenarios and insulin infusions. Model equations are then solved to yield the output variables (physiological biosignals, blood glucose concentration, CGM, and plasma insulin concentration).

Conclusions

A multivariable T1D simulator allows for rapid prototyping of physical activity-oriented AP system that can utilize physiological signals such as heart rate or energy expenditure in their algorithms.

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INFLUENCE OF ATHLETIC COMPETITION STRESS ON GLYCEMIC RESPONSE IN RECREATIONAL ATHLETES WITH TYPE 1 DIABETES

Session Type
ORAL PRESENTATION SESSION
Date
22.02.2020, Saturday
Session Time
08:30 - 10:00
Channel
London
Lecture Time
09:20 - 09:30

Abstract

Background and Aims

People with type 1 diabetes (T1D) have personal strategies for maintaining euglycemia while exercising which will serve them well during training. Their strategy often yields wildly differing results during a competition. The influence of competition stress (notably, epinephrine causing prompt elevations in glucose) and high-intensity and/or long-duration efforts can yield dysglycemia.

Methods

Recreational athletes with T1D were recruited for the study. A total of 5 runners (2M/3F) with 9 races have been studied to date. Participants completed an exercise stress test, an athletic competition, and a training run at the same pace as the athletic competition for a shorter duration and without the stress of the race. The carbohydrate and insulin intake prior to the athletic competition and the non-competitive race-intensity run were matched.

Results

The observed competition glucose trends are similar or elevated compared to the non-competition glucose trends of the same intensity at all distances studied. Within competitions for the same individual, in some cases the elevation observed during competition is not consistent despite reports of a similar level of stress in both competitions. When comparing these two cases, elevated heart rate in the race compared with the training session was correlated with elevated glucose in some individuals. Fewer hypoglycemic events were observed during athletic competitions than in non-competitive exercise sessions.

Conclusions

Competition stress may lead to an elevated glucose trend. Perceived stress level as reported by the individual is insufficient for determination of glycemia whereas an elevated heart rate may indicate an increase in glycemia at same running pace.

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