Imagine a smart bandage that doesn't just record your heart or brain activity but actually understands what the signals mean right on the skin. Instead of sending data to a bulky computer, it uses a special kind of 'green' plastic electronics that mimic how the brain processes information. This makes the device flexible, sustainable, and capable of spotting health issues privately and instantly.
Current bio-signal monitors are often rigid, power-hungry, and require external computers to process data, which compromises patient comfort and data privacy.
A flexible organic electronics platform featuring OTFT and OECT sensors and classification circuits. Deliverables include test structures for circuit design and organic electronic flexible sensors for low-noise signal recording.
If you are a wearable health tech manufacturer dealing with high power consumption in bio-sensors — this project developed low-power green AI sensors that classify electrophysiological signals directly on a flexible patch. This allows for continuous, private monitoring of patients without needing heavy external processing hardware.
If you are a flexible circuit producer dealing with the environmental impact of traditional silicon chips — this project developed a fully organic, environmentally sustainable platform for computing. It uses Thin Organic Large Area Electronics (TOLAE) processes to create circuits with approximately 100 transistors.
If you are a remote patient monitoring service dealing with data privacy and bandwidth issues — this project developed on-chip classification for bio-signals. By transforming data at the edge, it ensures private monitoring of signals like EEG before any data leaves the device.
Based on available project data, specific cost figures are not provided, although the project aims for 'low cost' using organic electronics and TOLAE processes.
The project focuses on developing 'scalable technologies on flexible substrates' using Thin Organic Large Area Electronics (TOLAE) processes.
Based on available project data, there is no specific mention of patents or licensing agreements, though the project involves an industrial advisory board for dissemination.
The technology is designed as a flexible patch that interfaces with the soft human body to detect and classify electrophysiological signals.
The project period runs from 2023-04-01 to 2026-09-30.
The consortium is heavily research-oriented, consisting of 9 partners across 3 countries (FR, DE, ES). It is dominated by academic and research institutions (5 universities and 3 research centers), with a low industry ratio of 11% (1 SME). This suggests the project is currently focused on fundamental technical breakthroughs rather than immediate commercial rollout.
Contact the CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) in France.
Contact us to find the specific SME partner in the consortium for licensing discussions.
