Project description
Building smart bioelectronic interfaces
Modern healthcare devices increasingly rely on AI to improve diagnosis and treatment. However, most AI systems depend on large, energy-hungry supercomputers located far from the point of care. At the same time, much of the information needed for these applications is found locally, within the body. This gap makes it challenging to create smart, personalised solutions that can adapt and learn over time. In this context, the ERC-funded NEURO-LABS project will combine organic neuromorphic engineering and bioelectronics. Specifically, it will develop a flexible platform that can monitor and control biosignals in real-time. Using advanced materials and biohybrid synapses, the research aims to demonstrate adaptive learning control on a soft robotic gripper, opening the door to innovative biointerfaces.
Objective
Artificial intelligence has demonstrated unprecedented advances in pattern and image recognition and is widely expected to significantly increase progress in smart healthcare devices, but continues to rely on inefficient supercomputers, operating remotely. On the other hand, relevant information for these applications mostly exists locally at the physiological level. Smart personalised bioelectronic applications can be tailored to a specific and unique case – or person – with the ability to be adapted, trained and optimised over time.
In this ERC project, organic neuromorphic engineering is combined with bioelectronics to achieve a tuneable neuromorphic platform, locally monitoring and modulating biosignals for the dynamic and adaptive learning control of a proof-of-principle soft robotic actuator.
Due to their compliant and non-linear characteristics soft actuators are difficult to model and thus present an ideal opportunity to demonstrate neuromorphic learning control. Organic electronic materials have been successfully implemented as building blocks in neuromorphic computing and bioelectronic applications. Particularly, mixed ionic-electronic conductors possess exceptional characteristics for use in biological environments.
At the interface between mechanical engineering, materials science, neuromorphic engineering and bioelectronics, neuro-labs will develop an organic neuromorphic platform, by optimisation of organic materials and circuits, and integration of sensors, neuromorphic devices, and microfluidics. We will develop a closed-loop adaptive biocircuit and demonstrate local tuning and neuromorphic learning control of a soft gripper. Finally, we will show optimised biocontrol of the gripper using biohybrid synapses modulated by the neurotransmitter environment, directly tuning the feedforward parameters in hardware. This will open a completely new field of adaptive neuromorphic biointerfaces and inspire a novel conceptual approach for learning control.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences physical sciences classical mechanics fluid mechanics microfluidics
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering computer hardware supercomputers
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
5612 AE Eindhoven
Netherlands
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