Neuromorphic EMG Processing with Spiking Neural Networks

Información del proyecto

NEPSpiNN

Identificador del acuerdo de subvención: 753470

DOI

10.3030/753470

Proyecto cerrado

Fecha de la firma de la CE 14 Marzo 2017

Fecha de inicio 1 Septiembre 2017

Fecha de finalización 31 Agosto 2019

Financiado con arreglo a

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coste total

€ 175 419,60

Aportación de la UE

€ 175 419,60

Coordinado por

UNIVERSITAT ZURICH
Switzerland

Periodic Reporting for period 1 - NEPSpiNN (Neuromorphic EMG Processing with Spiking Neural Networks)

Período documentado: 2017-09-01 hasta 2019-08-31

Resumen del contexto y de los objetivos generales del proyecto

The NEPSpiNN project aimed to realize a neuromorphic event-based neural processing system
that can directly interface with a commercial surface selectromyography (EMG) for hand gesture
classification. The proposed neuromorphic event-based processing classified the hand gestures in
a single step through a full custom hardware implementation of a spiking neural network (SNN)
which extracts spatio-temporal information of EMG signals locally in real-time with very low
power consumption.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

The general objective of the project was to exploit the low-power and low-latency features of a spiking neural network implemented in a mixed analog/digital neuromorphic chip for hand gesture classification.
Main results:
1) develop a spiking neural network able to process EMG signals
2) collection of 3 datasets (open access, zenodo) of EMG from the forearm
3) development and investigation of spiking recurrent neural network on chip
4) mobile application for sensor fusion (EMG+images) for neuroprosthetic control
5) spiking motor controller

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

The project was the first using neuromorphic chip for biomedical applications. It was the first one that was using hardware spiking neural network for EMG classification.
The results of the project have high research and commercial exploitation potentialities. The research area of exploitation was primary neuromorphic engineering and neurorobotics. The project results are a step towards the applications of neuromorphic devices in real-world scenarios, in particular for biomedical applications. This will have a high impact on health and science. The commercial areas of exploitation will be information technology, biomedical applications, prosthetic devices, and real-time computing. During the project development, the researcher already established collaborations with industrial partners that can result in new patents and technology transfer to products that can be introduced in the market.

General project description