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Gaussian process modelling of blood glucose response to free-living physical activity data in people with type 1 diabetes

Gaussian process modelling of blood glucose response to free-living physical activity data in people with type 1 diabetes
Gaussian process modelling of blood glucose response to free-living physical activity data in people with type 1 diabetes
Good blood glucose control is important to people with type 1 diabetes to prevent diabetes-related complications. Too much blood glucose (hyperglycaemia) causes long-term micro-vascular complications, while a severe drop in blood glucose (hypoglycaemia) can cause life-threatening coma. Finding the right balance between quantity and type of food intake, physical activity levels and insulin dosage, is a daily challenge. Increased physical activity levels often cause changes in blood glucose due to increased glucose uptake into tissues such as muscle. To date we have limited knowledge about the minute by minute effects of exercise on blood glucose levels, in part due to the difficulty in measuring glucose and physical activity levels continuously, in a free-living environment. By using a light and user-friendly armband we can record physical activity energy expenditure on a minute-by-minute basis. Simultaneously, by using a continuous glucose monitoring system we can record glucose concentrations. In this paper, Gaussian Processes are used to model the glucose excursions in response to physical activity data, to study its effect on glycaemic control
4913-4916
IEEE
Valletta, John Joseph
47edb52a-ada5-487b-96bf-21b474c892c2
Chipperfield, Andrew J.
524269cd-5f30-4356-92d4-891c14c09340
Byrne, Christopher D.
1370b997-cead-4229-83a7-53301ed2a43c
Valletta, John Joseph
47edb52a-ada5-487b-96bf-21b474c892c2
Chipperfield, Andrew J.
524269cd-5f30-4356-92d4-891c14c09340
Byrne, Christopher D.
1370b997-cead-4229-83a7-53301ed2a43c

Valletta, John Joseph, Chipperfield, Andrew J. and Byrne, Christopher D. (2009) Gaussian process modelling of blood glucose response to free-living physical activity data in people with type 1 diabetes. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE. pp. 4913-4916 .

Record type: Conference or Workshop Item (Paper)

Abstract

Good blood glucose control is important to people with type 1 diabetes to prevent diabetes-related complications. Too much blood glucose (hyperglycaemia) causes long-term micro-vascular complications, while a severe drop in blood glucose (hypoglycaemia) can cause life-threatening coma. Finding the right balance between quantity and type of food intake, physical activity levels and insulin dosage, is a daily challenge. Increased physical activity levels often cause changes in blood glucose due to increased glucose uptake into tissues such as muscle. To date we have limited knowledge about the minute by minute effects of exercise on blood glucose levels, in part due to the difficulty in measuring glucose and physical activity levels continuously, in a free-living environment. By using a light and user-friendly armband we can record physical activity energy expenditure on a minute-by-minute basis. Simultaneously, by using a continuous glucose monitoring system we can record glucose concentrations. In this paper, Gaussian Processes are used to model the glucose excursions in response to physical activity data, to study its effect on glycaemic control

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Published date: 2 September 2009
Venue - Dates: 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, United States, 2009-09-02 - 2009-09-06

Identifiers

Local EPrints ID: 71741
URI: http://eprints.soton.ac.uk/id/eprint/71741
PURE UUID: 23b1605e-b98a-425a-bd72-1d4ad139a98e
ORCID for Andrew J. Chipperfield: ORCID iD orcid.org/0000-0002-3026-9890
ORCID for Christopher D. Byrne: ORCID iD orcid.org/0000-0001-6322-7753

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Date deposited: 05 Jan 2010
Last modified: 14 Mar 2024 02:47

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Author: John Joseph Valletta

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