Periodic Reporting for period 1 - H2TRAIN (Enabling digital technologies for Holistic Health-lifestyle motivational and assisTed supeRvision supported by Artificial Intelligence Networks)
Reporting period: 2024-05-01 to 2025-04-30
The H2TRAIN initiative aligns with the ECS Strategic Research and Innovation Agenda 2023 (ECS-SRIA) objectives and tackles the core challenges of integrating digital technologies into a comprehensive health-oriented lifestyle, enhanced by artificial intelligence (AI) networks. This project pioneers the use of onedimensional and two-dimensional materials (1DM and 2DM) to create autonomous biosensors withinestablished CMOS technology layers, laying the groundwork for the expansion of AI-powered electronic health services and Internet of Things (IoT) applications focused on health, well-being, and the digital community. H2TRAIN's scope extends beyond facilitating digital technology; it innovates in the development of novel energy detection, collection, and storage mechanisms. These advancements are pivotal for incorporating sports and health activities into IoT solutions as part of wearable technology, achieved through the fusion of textile physics and smart system integration, including software and AI algorithm implementation. Moreover, the project's proposed solutions will undergo design, testing, and validation from both medical and sports science perspectives, significantly informed by insights from social sciences and humanities. Input from end-user groups and collaboration with relevant stakeholders will be sought throughout the development process. By focusing on three practical scenarios—remote assisted living, amateur sports training, and post-operative monitoring—H2TRAIN strives to catalyze the innovative capabilities of digital technologies within the smart healthcare sector, which often faces investment challenges in semiconductor nanofabrication due to the typically small scale of medical applications.
Keywords: Internet of Things (IoT), artificial intelligence (AI), edge computing, embedded intelligence, more-than-Moore devices, heterogeneous integration of functionality, biosensing devices, energy harvesting, 1D and 2D-materials.
Keywords: Internet of Things (IoT), artificial intelligence (AI), edge computing, embedded intelligence, more-than-Moore devices, heterogeneous integration of functionality, biosensing devices, energy harvesting, 1D and 2D-materials.
During the first reporting period, H2TRAIN made significant progress:
Biosensor Design and Prototyping: Developed and lab-tested multiple biosensors using graphene oxide and other nanomaterials.
Smart Textile Integration: Embedded biosensors in textile platforms with initial validations (e.g. ECG, EMG, SpO2).
Energy Subsystems: Prototypes for energy harvesting (TEG, PZT, RF) and energy storage (supercapacitors) were fabricated and partially validated.
AI Development: Edge-based AI modules were implemented for biometric recognition and sensor calibration.
Use Case Pilots: User requirements were defined, and early-stage field testing has begun in healthcare and sports settings.
Dissemination and Exploitation: Over 25 conference participations, 24 scientific articles submitted, and the launch of public engagement through the website and social media.
These results are foundational to achieving higher Technology Readiness Levels (TRL) and confirming feasibility across multiple disciplines.
Biosensor Design and Prototyping: Developed and lab-tested multiple biosensors using graphene oxide and other nanomaterials.
Smart Textile Integration: Embedded biosensors in textile platforms with initial validations (e.g. ECG, EMG, SpO2).
Energy Subsystems: Prototypes for energy harvesting (TEG, PZT, RF) and energy storage (supercapacitors) were fabricated and partially validated.
AI Development: Edge-based AI modules were implemented for biometric recognition and sensor calibration.
Use Case Pilots: User requirements were defined, and early-stage field testing has begun in healthcare and sports settings.
Dissemination and Exploitation: Over 25 conference participations, 24 scientific articles submitted, and the launch of public engagement through the website and social media.
These results are foundational to achieving higher Technology Readiness Levels (TRL) and confirming feasibility across multiple disciplines.
H2TRAIN delivers several innovations that extend current capabilities:
Novel 2D/1D-material biosensors with CMOS compatibility and machine learning-based calibration.
Secure biometric key generation using embedded AI and physiological signal fusion.
Edge-cloud continuum architecture supporting real-time inference in wearables.
Hybrid energy harvesting systems (thermoelectric, piezoelectric, RF) integrated into textiles.
High recyclability and washability in smart textile electronics for long-term sustainability.
These outcomes enable AIoT systems that go beyond the conventional capabilities of consumer wearables, and represent breakthroughs in both embedded systems and digital health.
Novel 2D/1D-material biosensors with CMOS compatibility and machine learning-based calibration.
Secure biometric key generation using embedded AI and physiological signal fusion.
Edge-cloud continuum architecture supporting real-time inference in wearables.
Hybrid energy harvesting systems (thermoelectric, piezoelectric, RF) integrated into textiles.
High recyclability and washability in smart textile electronics for long-term sustainability.
These outcomes enable AIoT systems that go beyond the conventional capabilities of consumer wearables, and represent breakthroughs in both embedded systems and digital health.