Enabling digital technologies for Holistic Health-lifestyle motivational and assisTed supeRvision supported by Artificial Intelligence Networks

H2TRAIN proposal is funded on the sixth edition of the Electronic Components and Systems (ECS) Strategic Research and Innovation Agenda (ECS-SRIA) topics and major challenges for enabling digital technologies in holistic health-lifestyle supported by artificial intelligence (AI) networks.

Biosensors for e-health and smart tracking of sport and fitness are a class of devices that is dominating the consumer and professional market with an unprecedented growth.

Despite the impressive capabilities of recent approaches, several prospective revolutionary improvements are still open points, mainly in relationship with four factors: sensing new biosignals and tracking new activity patterns; improving battery lifetime and energy management for continuous use; and secure, reliable and efficient data analysis with AI algorithms and connectivity with the IoT.H2TRAIN aims at advancing the state of the art in this respect, taking profit from the remarkable properties and synergistic potential of one-dimensional (1D) and two-dimensional (2D) materials (1DM and 2DM), enabling more sensitive, efficient, and miniaturized biosensing capabilities within the established CMOS technology framework.

This will contribute to the growth of e-health services assisted by AI and will fortify the development of Internet of Things (IoT) applications in health & wellbeing and digital society.

H2TRAIN not only facilitates digital technology but also involves the development of new 1DM and 2DM-based devices for sensing, energy harvesting and supercapacitor storage.

These innovations serve to integrate sport and health activities into IoT applications, making them accessible as wearable technology.

H2TRAIN combines mature CMOS technology products for health and sport sensing with embedded intelligence as a cross-sectional technology.

This combination offers a broad spectrum of technology demonstrators (TD) based on advanced sensors, such as tattoo sweat, C-reactive protein, cortisol and lactate.