FI-STAR EXPOSE - cloud based solution for eHealth

The project aims to develop, test and validate a cloud based solution for processing of real-time multiple patient data that can make automated decisions and alert the health provider about the current, or upcoming, worsening of the patient condition. 

We call the solution “Exacerbation prediction engine”. The engine will be able to make decisions based on the changes in multiple parameters simultaneously even in the cases when a single parameter analysis is not indicating any deterioration/exacerbation of patient’s health. The engine will be applicable to any FI-STAR use-case using multiple sensors/inputs and suitable for making automated decisions.

The engine will be able to analyze a large set of data coming from the sensors and patient health forms, perform initial filtering, analyze the data and, using a pre-defined set of rules, make a decision on whether the health provider should be contacted. The engine will also be used for finding new sets of data values which precede exacerbations using appropriate data mining algorithms in combination with predictive analytics and/or machine learning. 

This cloud-based solution will be compared and benchmarked against the Swedish COPD solution in terms of functionality, performance, scalability (including a relevant social impact), security and economics. The solution will also be verified for applicability to FI-STAR use cases for cardiology (Romania) and diabetes (Norway), with extension to other FI-STAR cases, where applicable.

F-STAR EXPOSE (Exacerbation Prediction Engine: early warning and decision making tool) is a sub-project of the Future Internet Social and Technological Alignment Research (FI-STAR) European project from EC Framework Programme 7. It is implemented jointly by Acreo Swedish ICT, with participation of SICS, and SIVECO Romania and runs from April 2014 till May 2015.

Collaborating partners

Acreo, SIVECO