ESR15 - Neuromorphic Embedded Processing for Touch

Identification of neural network architectures for reproducing biological receptive field responses and implementation in neuromorphic hardware.

TAGS   Biological Touch   Prosthetics   Technologies for Touch

Overview

Objectives

Identification of neural network architectures for reproducing biological receptive field responses and implementation in neuromorphic hardware. Design, simulation, fabrication and characterization of neuromorphic circuits for spike-based computation of tactile sensory data. Evaluation of network performances with methods used in computational neuroscience to infer the information content about the stimulus (see Research Theme 6). Integration with sensors developed in Research Themes 13 and 14.

Expected Results

I will design and develop novel neuromorphic circuits and systems for emulating biological tactile sensing. To this end the modeling work performed in WP1 will be adapted to the analog VLSI implementation; furthermore, suitable interfaces to the sensors developed in WP3 will be designed. The final embedded system, targeted at reproducing biological RF responses, will substantially advance the state-of-the-art.

Secondments

  • IIT-CNCS

    learn SNN models

  • UOG

    integration of RF hardware with nanowire FET devices

  • OSSUR

    integration on prosthetic device

Supervisors

  • E. Chicca

  • R. Dahiya

  • S. Panzeri

  • Á. Alexandersson

Michele Mastella

The comparison between different approaches, followed by humans and by nature in problem solving, always charmed me. I have always wanted to merge these two worlds in order to create new structures. I, therefore, decided to pursue my idea in the neuromorphic engineering area.

Neutouch for me

Neutouch collects together different ingredients for a potential great recipe: lot of students with different expertise, distributed across Europe and willing to collaborate in a shared project.

Info

  • Research Topics

    Neuromorphic Circuit, Spiking Neural Network

  • Institution

    University of Groningen

  • Background

    B.Sc. Electronic engineering (Politecnico di Milano, 2013-2016)
    M.Sc. Electronic engineering (Politecnico di Milano, 2016-2019)

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 813713 ).
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