115 citations · 125 across the 3 of their papers we have counts for
5 papers
A novel hand-held interface supporting the self-management of Type 1 diabetes
Robert Spence, Chukwuma Uduku, Kezhi Li +2
The paper describes the interaction design of a hand-held interface supporting the self-management of Type 1 diabetes. It addresses well-established clinical and human-computer int…
Basal Glucose Control in Type 1 Diabetes using Deep Reinforcement Learning: An In Silico Validation
Taiyu Zhu, Kezhi Li, Pau Herrero +1
People with Type 1 diabetes (T1D) require regular exogenous infusion of insulin to maintain their blood glucose concentration in a therapeutically adequate target range. Although t…
A Dual-Hormone Closed-Loop Delivery System for Type 1 Diabetes Using Deep Reinforcement Learning
Taiyu Zhu, Kezhi Li, Pantelis Georgiou
We propose a dual-hormone delivery strategy by exploiting deep reinforcement learning (RL) for people with Type 1 Diabetes (T1D). Specifically, double dilated recurrent neural netw…
Convolutional Recurrent Neural Networks for Glucose Prediction
Kezhi Li, John Daniels, Chengyuan Liu +2
Control of blood glucose is essential for diabetes management. Current digital therapeutic approaches for subjects with Type 1 diabetes mellitus (T1DM) such as the artificial pancr…
Body Dust: Miniaturized Highly-integrated Low Power Sensing for Remotely Powered Drinkable CMOS Bioelectronics
Sandro Carrara, Pantelis Georgiou
The aim of this paper is to introduce current advances in technology that could enable the development of fully drinkable and autonomous bio-electronic CMOS sensors in the form of…