TrackMyHealth

Integrated Support System for the Elderly, for people with health problems and lonely workers by Utilizing Wearable Devices and Machine Learning Algorithms

Short title: TrackMyHealth

Code of Act (Project): ΗΠ1ΑΒ-00127

Scientifically Responsible: Prof. Chrysostomos Stylios

Start date: 25/09/2018

End date: 13/07/2022

Budget: 146.127,50 €

Funding framework: Structural Fund Partnership Agreement for the Development Framework (PA). 2014-2020, Regional Operational Programme “Epirus”, European Regional Development Fund (ERDF)

Short description: The TrackMyHealth project proposes an integrated monitoring and support system for individuals (elderly, lonely workers) utilising wearables and machine learning algorithms. The system is an easy-to-use solution for users as it consists of a wearable device (wristwatch) that does not interrupt/burden the flow of activities of each individual and an application developed for smartphones (mobile app) that does not require specialized knowledge for its operation. This project uses a device that has a heart rate sensor as well as motion detection sensors (accelerometer, gyroscope).

Objectives:

Conducting extensive literature review on state-of-the-art technologies and methodologies used internationally for fitness monitoring.
Design and development of advanced methodologies and machine learning models for the “smart” monitoring & evaluation of the physical condition of elderly and lonely workers utilizing wearable and mobile devices.
Design and development of an advanced mobile application, which uses signals from sensors integrated into wearable devices to identify the activities performed and assess health and fitness levels in real-time.
Automated sensory / motor control to detect and prevent dangerous and critical for the health of the supervised user conditions (e.g., abrupt change of heart rate at rest, elderly falls, etc.).
Automated sending of alerts in case of need to caregivers/health supervisors for immediate intervention in case of emergency.
Design and development of a web platform for monitoring and providing effective real-time support by the health supervisor. In addition, the opportunity to monitor the health history of users is provided and to automatically inform the interested parties.

Expected outcomes:

Health monitoring and personal fitness improvement (self-monitoring) using the mobile application.
Evaluation of the basic health levels and feedback (from the system) based on reliable machine learning and decision-making algorithms.
Prevention of dangerous health situations and promotion of well-being.
Continuous remote monitoring of people who need help or are in need by health supervisors.
Automatic notification (sending notifications) in cases of immediate danger for intervention/providing help where necessary.

The Program is co-financed by the European Union And from the National Resources of the participating States