Diabetes Mellitus, Type 1 Clinical Trial
Official title:
Adaptive, Real-time, Intelligent System to Enhance Self-care of Chronic Disease
The Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic diseases (ARISES) project will use type 1 diabetes (T1DM) as an exemplary case study to demonstrate safety, technical proof of concept and efficacy of a novel mobile platform. Combining wearable sensors and smartphone technology, a range of biological, environmental and behavioural data will be analysed to provide real-time therapeutic and lifestyle decision support. Using Case-Based-Reasoning (CBR), the system will be adaptive and personalised with the ability to learn from previously encountered scenarios. Ultimately, ARISES aims to empower self-management of chronic illness and limit the complications associated suboptimal treatment.
ARISES will target self-management to optimise glucose control through insulin dose
recommendation (therapeutic advice), exercise and stress support, hypoglycaemia prevention
through timely snack recommendation and behavioural change through educational support
(lifestyle advice).
Semi-structured focus meetings comprised of patients with T1DM, clinicians, engineers and
experts in human-computer interaction will provide a forum to establish the essential
usability requirements to incorporate into the ARISES mobile interface. The design will focus
on ensuring access to decision support is intuitive and efficient while maintaining sight of
real-time glycaemia outcomes. The design and implementation of the user-interface will be
assessed in a series of usability validation studies.
Clinical studies will be conducted in two phases. The first phase will be an observational
study using wearable technologies to collect data and evaluate blood glucose correlations
against physiological and environmental case parameters. Useful associations will assist the
development of the CBR/machine learning algorithm and identify wearable devices for the final
ARISES platform.
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