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Part 1: Design of a Diameter Dashboard displaying personalized blood glucose levels, physical activity, and nutritional data for type 2 diabetes patients. Part 2: Development of an algorithm to predict blood glucose values integrating glucose parameters, activity, and nutritional data using machine learning techniques.

Peters, S.F. (2023) Part 1: Design of a Diameter Dashboard displaying personalized blood glucose levels, physical activity, and nutritional data for type 2 diabetes patients. Part 2: Development of an algorithm to predict blood glucose values integrating glucose parameters, activity, and nutritional data using machine learning techniques.

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Abstract:In a collaborative T2D study Ziekenhuisgroep Twente (ZGT), the University of Twente (UT) and the Roessingh Research and Development (RRD) collected data from participating patients with T2D from three different sources; Blood Glucose (BG) sensors, nutritional diaries and physical activity tracking. The individual data sources were then merged into one application, the Diameter Application (DA). To make the raw data readily accessible for use during patient consults, a dashboard needed to be designed to visualize and provide convenient access to all the collected lifestyle data in the DA. During the design process feedback was requested to improve on each design. Through visualization of the collected data in one dashboard, patients are instantly informed of their blood glucose status, nutrition intake and physical activity parameters which can work as an encouragement to make necessary changes in nutrition intake and/or physical activity. The Diameter Dashboard (DD) is an important first step towards encouraging patients’ to self-manage their lifestyle and for healthcare workers to be able to coach and to care for T2D patients.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine, 50 technical science in general
Programme:Biomedical Engineering MSc (66226)
Link to this item:https://purl.utwente.nl/essays/97919
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