Optimising Personalised Medical Insights by Introducing a Scalable Health Informatics Application for Sensor Data Extraction, Preprocessing, and Analysis.

Wearable sensors, among other informatics solutions, are readily accessible to enable noninvasive remote monitoring in healthcare. While providing a wealth of data, the wide variety of such sensing systems and the differing implementations of the same or similar sensors by different developers complicate comparisons of collected data. An online application as a platform technology that provides uniform methods for analysing balance data is presented as a case study.

A Reinforcement Learning Based System for Blood Glucose Control without Carbohydrate Estimation in Type 1 Diabetes: In Silico Validation.

Type 1 Diabetes (T1D) is a chronic autoimmune disease, which requires the use of exogenous insulin for glucose regulation. In current hybrid closed-loop systems, meal entry is manual which adds cognitive burden to the persons living with T1D. In this study, we proposed a control system based on Proximal Policy Optimisation (PPO) that controls both basal and bolus insulin infusion and only requires meal announcement, thus eliminating the need for carbohydrate estimation.

Integrating Multiple Inputs Into an Artificial Pancreas System: Narrative Literature Review.

Background: Type 1 diabetes (T1D) is a chronic autoimmune disease in which a deficiency in insulin production impairs the glucose homeostasis of the body. Continuous subcutaneous infusion of insulin is a commonly used treatment method. Artificial pancreas systems (APS) use continuous glucose level monitoring and continuous subcutaneous infusion of insulin in a closed-loop mode incorporating a controller (or control algorithm).

A Wearable System to Analyze the Human Arm for Predicting Injuries Due to Throwing.

There is limited understanding on factors that contribute to throwing related injuries that frequently occur in sports such as Baseball, Cricket and Javelin throwing.This preliminary study focuses on the development of a real time wearable system focusing on extracting key parameters related to potential upper arm injuries associated with the throwing action in the game of Cricket. A wearable system is developed to analyze Electromyography (EMG) signals for detecting muscle activity and Inertial Measurement Unit (IMU) data for monitoring the arm motion.