Methods for combining continuously measured glucose and activity data in people with Type 2 diabetes: challenges and solutions

Research output: Contribution to journalArticle

Abstract

Aims: To present the novel application of combining continuously measured glucose with continuous accelerometer measured physical activity and sedentary behaviour data and discusses the principles used and challenges faced in combining and analysing these two sets of data in the context of diabetes management.
Methods: The background and rationale for exploring glucose, physical activity and sedentary behaviour in people with Type 2 diabetes is presented, the paper outlines the technologies used, the individual data extraction and finally the combined data analysis. A case study approach is used to illustrate the application of the combined data processing and analysis.
Results: The data analytic principles used could be transferred to different conditions where continuous data sets are being combined to help individuals or health professionals better manage and care for people with long term conditions.
Conclusions: Future work should focus on generating validated techniques to visualise combined data sets and explore ways to present data back to the individual in an effective way to support health care management and rehabilitation.
LanguageEnglish
Number of pages6
Journal Journal of Rehabilitation and Assistive Technologies Engineering
Volume5
Early online date9 Sep 2018
DOIs
Publication statusE-pub ahead of print - 9 Sep 2018

Fingerprint

Type 2 Diabetes Mellitus
Glucose
Rehabilitation
Technology
Delivery of Health Care
Health
Datasets

Keywords

  • type 2 diabetes
  • diabetes
  • physical activity
  • sedentary behavior
  • diabetes management
  • mHealth
  • technology
  • mobile technology

Cite this

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title = "Methods for combining continuously measured glucose and activity data in people with Type 2 diabetes: challenges and solutions",
abstract = "Aims: To present the novel application of combining continuously measured glucose with continuous accelerometer measured physical activity and sedentary behaviour data and discusses the principles used and challenges faced in combining and analysing these two sets of data in the context of diabetes management. Methods: The background and rationale for exploring glucose, physical activity and sedentary behaviour in people with Type 2 diabetes is presented, the paper outlines the technologies used, the individual data extraction and finally the combined data analysis. A case study approach is used to illustrate the application of the combined data processing and analysis. Results: The data analytic principles used could be transferred to different conditions where continuous data sets are being combined to help individuals or health professionals better manage and care for people with long term conditions. Conclusions: Future work should focus on generating validated techniques to visualise combined data sets and explore ways to present data back to the individual in an effective way to support health care management and rehabilitation.",
keywords = "type 2 diabetes, diabetes, physical activity, sedentary behavior, diabetes management, mHealth, technology, mobile technology",
author = "McMillan, {Kathryn A} and Alison Kirk and Allan Hewitt and Sandra MacRury and Marilyn Lennon",
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T2 - Journal of Rehabilitation and Assistive Technologies Engineering

AU - McMillan, Kathryn A

AU - Kirk, Alison

AU - Hewitt, Allan

AU - MacRury, Sandra

AU - Lennon, Marilyn

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Y1 - 2018/9/9

N2 - Aims: To present the novel application of combining continuously measured glucose with continuous accelerometer measured physical activity and sedentary behaviour data and discusses the principles used and challenges faced in combining and analysing these two sets of data in the context of diabetes management. Methods: The background and rationale for exploring glucose, physical activity and sedentary behaviour in people with Type 2 diabetes is presented, the paper outlines the technologies used, the individual data extraction and finally the combined data analysis. A case study approach is used to illustrate the application of the combined data processing and analysis. Results: The data analytic principles used could be transferred to different conditions where continuous data sets are being combined to help individuals or health professionals better manage and care for people with long term conditions. Conclusions: Future work should focus on generating validated techniques to visualise combined data sets and explore ways to present data back to the individual in an effective way to support health care management and rehabilitation.

AB - Aims: To present the novel application of combining continuously measured glucose with continuous accelerometer measured physical activity and sedentary behaviour data and discusses the principles used and challenges faced in combining and analysing these two sets of data in the context of diabetes management. Methods: The background and rationale for exploring glucose, physical activity and sedentary behaviour in people with Type 2 diabetes is presented, the paper outlines the technologies used, the individual data extraction and finally the combined data analysis. A case study approach is used to illustrate the application of the combined data processing and analysis. Results: The data analytic principles used could be transferred to different conditions where continuous data sets are being combined to help individuals or health professionals better manage and care for people with long term conditions. Conclusions: Future work should focus on generating validated techniques to visualise combined data sets and explore ways to present data back to the individual in an effective way to support health care management and rehabilitation.

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KW - physical activity

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