ARISES Phase 2
Research type
Research Study
Full title
Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic diseases
IRAS ID
271127
Contact name
Nick Oliver
Contact email
Sponsor organisation
Imperial College London
Clinicaltrials.gov Identifier
Duration of Study in the UK
0 years, 7 months, 1 days
Research summary
The Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic diseases (ARISES) is a novel mobile platform capable of collecting data from multiple sources to empower people to more effectively self-manage chronic disease through therapeutic and lifestyle decision support. Using wearable sensors and smartphone technology, a wide range of biological, environmental and behavioural data will feedback into the system to facilitate local real-time decision support and adaptive personalised care using artificial intelligence (AI) machine based learning. The ARISES AI algorithm will run locally on a smartphone device. The system will be designed to offer decision support applicable and specific to people with T1DM receiving MDI and CSII methods of insulin delivery.
ARISES aims to use participants with T1DM as an exemplar case study. The system will target self-management to optimise glucose control through dynamic real-time 1-hour glucose prediction, insulin dose recommendation (therapeutic advice), exercise and physical stress support, hypoglycaemia prevention through timely carbohydrate and snack recommendation and behavioural change through educational measures (lifestyle advice). Measures to safeguard patients will be ensured through education, predictive glucose alarm and carbohydrate recommendation. Participants with T1DM will be recruited as part of the design team to offer feedback on user requirements and ergonomic interface development throughout the project.
REC name
London - Brent Research Ethics Committee
REC reference
20/LO/0071
Date of REC Opinion
3 Apr 2020
REC opinion
Further Information Favourable Opinion