SOURCE-LINKED INTELLIGENCE

Neuromorphic Learning in Organic Adaptive Biohybrid Systems

CORDIS · observation · Publication date unknown

Neuromorphic Learning in Organic Adaptive Biohybrid Systems 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 mod

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recordType

award

status

SIGNED

region

EU

value

1996143

unit

EUR