Project Description

EK2.0 develops artificial intelligence algorithms that, based on the remote monitoring of the behaviour and health conditions of the chronic, fragile or dependent patient, enable the creation of new management tools and solutions for healthcare professionals.

These algorithms provide added value to the current functionalities of the systems used in the clinical and care environment by allowing the integration and learning from data collected by sensors that capture environmental information and personal health or physical activity data, for its integration with the available clinic history data.

The results of the project will be used for the implementation of new tools on an open and interoperable platform to support healthcare professionals’ daily activities inside and outside the hospital, as well as to help on decision-making processes. The developed platform will allow both the incorporation of new data sources and the interconnection to other systems, such as emotional recognition systems or analysis of biometric parameters.

The project counts with a consortium formed by Seidor, a leading multinational in management software consulting solutions, and Eurecat, through its Valorisation Department and eHealth Technological Unit.

General details

Project

EK2.0 – Implementation of artificial intelligence algorithms applied to both clinical and social information management systems with the aim of developing new tools for remote predictive healthcare and decision-making support in fragile and/or dependency environments.

Project reference

RTC-2017-6677-1

Programme and call for tender

Project financed by the MINISTRY OF SCIENCE, INNOVATION AND UNIVERSITIES and by the European Union, within the framework of the call Retos-Collaboration of the State Program of Research, Development and Innovation Oriented to the Challenges of Society, within the State Research Plan Scientific and Technical and Innovation 2013-2016, with the main objective of promoting technological development, innovation and quality research.

FEDER