ARISES
Research type
Research Study
Full title
Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic disease
IRAS ID
240662
Contact name
Nick Oliver
Contact email
Sponsor organisation
Imperial College London
Duration of Study in the UK
2 years, 2 months, 3 days
Research summary
The diabetes technology group at Imperial College aim to use type 1 diabetes (T1DM) as an exemplary case study to demonstrate safety, technical proof of concept and efficacy of an Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic diseases (ARISES). The smartphone-based system will combine wearable sensors and analyse a range of biological, environmental and behavioural data to provide real-time therapeutic and lifestyle decision support through a newly designed user-friendly application. Integrating a new decision support algorithm based on case-based reasoning (CBR) and machine learning artificial intelligence technology, ARISES will be adaptive, personalised and able to learn from previously encountered scenarios. Ultimately, ARISES aims to empower self-management of chronic illness and limit the complications associated suboptimal treatment.
T1DM self-management will be targeted by optimising 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).
The first phase of the study will involve using wearable technologies to record environmental parameters (geolocation and ambient temperature), vital body signs (heart rate, skin temperature, motion, nervous system activity) and identify correlations with monitored blood glucose levels in 12 participants with T1DM. Useful associations will assist the development of the ARISES CBR algorithm.
Semi-structured focus meetings comprised of 10 patients with T1DM 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 while maintaining sight of real-time glycaemia outcomes. Focus meetings will run for the duration of the study and will be observed by a clinician, engineer and expert in human-computer interaction.
The approval and outcomes derived from the first phase observational study and focus groups are required for designing the final feasibility clinical study and user-interface validation studies.
REC name
London - Fulham Research Ethics Committee
REC reference
18/LO/1096
Date of REC Opinion
16 Jul 2018
REC opinion
Further Information Favourable Opinion