CARES

Project Description

The international research project CARES—“Community Access & Remote Empowerment for Self-care”—focuses on the development of an integrated, AI-supported system for the continuous collection and analysis of health-related data.

In the home environment, modern sensors and medical monitoring devices are used to track, among other things, heart rate, blood pressure, oxygen saturation, body weight, sleep, physical activity, and movement patterns. As part of this, the partner Localino (Schmallenberg) is developing a novel tracking

sensor that can be used, for example, to track movement and activity.

The Canadian partner HealthEspresso (Toronto) will consolidate and visualize all this information via its app platform.

Statistical methods and machine learning techniques will be used to identify correlations between vital signs, movement, and daily behavior. Based on these findings, health indicators and predictive models will be developed.

The University of Siegen will be responsible in particular for developing suitable predictive models as well as selecting and implementing appropriate machine learning algorithms.

In the long term, the developed system is intended to help identify changes in health at an early stage, support preventive measures, and enable more personalized and community-based healthcare.

Key Focus Areas of the Project

• Continuous collection of vital signs, activity, and movement data

• Integration of medical monitoring devices with motion and location sensors

• Secure integration and visualization of health-related data

• Development of statistical trend analyses and appropriate health indicators

• Use of artificial intelligence to detect changes in health

• Development of short-, medium-, and long-term predictive models

• Support for prevention and self-managed health care