Exploring the classification of biomedical signals using plasticity in recurrent networks of ...

Continuous monitoring of physiological biomarkers could help to detect and diagnose several health conditions at their early stages, such as cardiovascular and neurological diseases and as a result real-time processing of biomedical signals in a low-power fashion is becoming increasingly important. Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequentiality and time-series data. Implementing RNNs on neuromorphic platforms can be a good solution to this problem. Starting from a simple RNN, we plan to investigate the spiking learning algorithms which can be implemented on a hardware platform. The final goal of the workgroup is to be able to classify EMG signals using BRIAN2 simulator.

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Day Time Location
Tue, 24.04.2018 19:00 - 20:00 Sala Panorama
Wed, 25.04.2018 19:00 - 20:00 Sala panorama
Thu, 26.04.2018 11:00 - 12:00 outside
Fri, 27.04.2018 21:00 - 00:00 Sala panorama
Sat, 28.04.2018 15:00 - 16:00 Sala Panorama
Mon, 30.04.2018 14:00 - 16:00 Sala Panorama
Wed, 02.05.2018 15:00 - 16:00 Panorama


Elisa Donati
Melika Payvand


Abhishek Banerjee
Simone Benatti
Karla Burelo
Erika Covi
Tamás Czimmermann
Thomas Dalgaty
Elisa Donati
Charlotte Frenkel
Richard George
Giacomo Indiveri
Sepp Kollmorgen
Brent Komer
Renate Krause
Christian David Márton
Johannes Partzsch
Melika Payvand
Saray Soldado Magraner
Michiel Van Dyck
Juan Camilo Vasquez Tieck
Jayawan Wijekoon
Borys Wrobel
Guido Zarrella