Displaying One Session

PARALLEL SESSION Webcast
Session Type
PARALLEL SESSION
Channel
London
Date
22.02.2020, Saturday
Session Time
10:30 - 12:00

Diet monitoring for gestational diabetes, weight-loss interventions and personalized nutrition

Session Type
PARALLEL SESSION
Date
22.02.2020, Saturday
Session Time
10:30 - 12:00
Channel
London
Lecture Time
10:30 - 10:55

Abstract

Background and Aims / Part 1

Healthy diet and regular physical activity are powerful tools to improve metabolic control in all types of diabetes and cardiometabolic syndrome risk. For that reason, patients’ treatments include aspects of behaviour change and the promotion of a healthy lifestyle.

Methods / Part 2

The use of information technologies can support the adoption of healthy diets and the acquisition of competences for meal planning, food selection and food preparation. Providing patients with better knowledge and education is possible to improve adherence to long-term lifestyle changes. Information about patients’ diet can also help physicians in the therapy change decision making but it is an information difficult to obtain, mainly because the registering process is manual and time demanding.

Results / Part 3

This talk will present some experiences of diet monitoring with different data registry requirements, from complete and comprehensive data logs at the level of ingredients to simplified and qualitative registering of diet transgressions that trigger intelligent alerts and recommendations.

Conclusions / Part 4

The use of web and mobile technologies for diet monitoring decreases the patient burden, increases patient knowledge and supports better decisions.

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Technologies and systems for meal counting and estimating prandial insulin dose

Session Type
PARALLEL SESSION
Date
22.02.2020, Saturday
Session Time
10:30 - 12:00
Channel
London
Lecture Time
10:55 - 11:20

Abstract

Background and Aims

Effective insulin therapy in people with diabetes requires them to be able to estimate post prandial insulin doses compensating for consumed meals. The aim of this work is to review existing technologies and systems for automating meal counting and estimating prandial insulin doses.

Methods

Automatic bolus calculators estimate prandial insulin doses based on carbohydrate content in meals and a carbohydrate-to-insulin ratio provided by the user. In recent years, several systems designed to automate the counting of meals, i.e. estimation of energy and carbohydrate content (in some cases also protein and fat) in a meal have been developed. In these systems several different technologies have been used such as food image processing and analysis, voice description of meals followed by voice-to-text conversion and the meal content analysis, or monitoring food intake activities (e.g. chewing or swallowing) using signal processing from various sensors.

Results

It was demonstrated in a few pilot clinical trials that systems for meal counting based on the computer vision and food image processing techniques or the voice description of meals are feasible and applicable. Using such systems it is possible to calculate content of meals with high enough accuracy to estimate insulin doses that effectively control postprandial glycemia. Whereas systems monitoring food intake activities are at the earlier stage of development and distinguishing a large number of foods using such systems is unlikely.

Conclusions

New insights on the effect of dietary macronutrients on postprandial glycemia demonstrates that prandial insulin doses should account for carbohydrates, protein and fat content in meals. Some of the technologies and systems outlined above may facilitate an accurate meal counting and thus, contribute to improvement of the insulin therapy results.

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Cracking the meal challenge – Insight from closed-loop studies

Session Type
PARALLEL SESSION
Date
22.02.2020, Saturday
Session Time
10:30 - 12:00
Channel
London
Lecture Time
11:20 - 11:45

Q&A

Session Type
PARALLEL SESSION
Date
22.02.2020, Saturday
Session Time
10:30 - 12:00
Channel
London
Lecture Time
11:45 - 12:00

Test

Session Type
PARALLEL SESSION
Date
22.02.2020, Saturday
Session Time
10:30 - 12:00
Channel
London
Lecture Time
12:00 - 12:00