SciTransfer
H2TRAIN · Project

AI-Powered Wearable Biosensors for Remote Health Monitoring and Sports Performance Tracking

healthTestedTRL 4

Imagine a smart shirt that doesn't just track your heart rate, but actually 'tastes' your sweat to check for stress or fatigue. It uses ultra-thin materials and tiny chips to sense chemicals in your body and powers itself using your own body heat or movement. This data is then processed by a built-in brain that tells you exactly how to adjust your training or health routine in real-time.

By the numbers
35
total partners
23
industry partners
19
SMEs
66%
industry ratio
The business problem

What needed solving

Current health wearables rely on generic data and frequent charging, failing to track critical biochemical markers like cortisol or lactate in real-time. This limits their use in professional sports and critical medical post-operative monitoring.

The solution

What was built

Lab-tested biosensors using graphene oxide, smart textile platforms for ECG/EMG/SpO2, and energy harvesting prototypes (TEG, PZT, RF).

Audience

Who needs this

Medical wearable manufacturersProfessional sports analytics firmsRemote patient monitoring companiesSmart textile developers
Business applications

Who can put this to work

Medical Devices
enterprise
Target: Post-operative care provider

If you are a care provider dealing with high readmission rates—this project developed biosensors for post-operative monitoring that track C-reactive protein and cortisol. This allows for continuous patient supervision without requiring hospital stays.

Sports Technology
mid-size
Target: Professional athletic apparel brand

If you are a brand dealing with generic fitness trackers—this project developed smart textiles with embedded sensors for lactate and sweat analysis. This provides amateur and pro athletes with precise biochemical data to optimize training.

Elderly Care
SME
Target: Remote assisted living service

If you are a service provider dealing with the difficulty of monitoring seniors at home—this project developed edge-based AI modules and biosensing devices. This enables autonomous health tracking and alerts for remote assisted living scenarios.

Frequently asked

Quick answers

What is the cost of implementing these sensors?

Based on available project data, specific pricing or cost-per-unit information is not provided.

Can this be produced at an industrial scale?

The project uses established CMOS technology layers, which are the industry standard for mass-producing semiconductors, suggesting a path toward industrial scalability.

How is the intellectual property handled or licensed?

Based on available project data, specific licensing terms are not mentioned, though the project involves 23 industry partners who likely share in the IP development.

How does the device stay powered during continuous use?

The project developed energy harvesting prototypes using TEG, PZT, and RF, along with supercapacitors for energy storage to extend battery life.

When will the technology be available for commercial use?

The project period runs from 2024-05-01 to 2027-04-30, indicating the development phase is ongoing.

Consortium

Who built it

The project is highly market-oriented, featuring a strong industry presence with 23 companies out of 35 total partners (a 66% industry ratio). The heavy involvement of 19 SMEs suggests a focus on agile commercialization and specialized technology niches. With partners across 7 countries, the consortium balances academic research from 7 universities with practical industrial application.

How to reach the team

Contact the Universidad de Las Palmas de Gran Canaria

Next steps

Talk to the team behind this work.

Contact us to connect with the H2TRAIN consortium for licensing and partnership opportunities.

More in Health & Biomedical
See all Health & Biomedical projects