Reference : A Brain-Machine Interface with an Innovative Spiking Neural Network Decoder
Scientific congresses and symposiums : Poster
Engineering, computing & technology : Electrical & electronics engineering
Engineering, computing & technology : Multidisciplinary, general & others
A Brain-Machine Interface with an Innovative Spiking Neural Network Decoder
Dethier, Julie mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Nuyujukian, Paul [Stanford University > Department of Bioengineering and School of Medicine > > >]
Elassaad, Shauki A. [Stanford University > Department of Bioengineering > > >]
Shenoy, Krishna V. [Stanford University > Department of Electrical Engineering, Department of Bioengineering, and Department of Neurobiology > > >]
Boahen, Kwabena [Stanford University > Department of Bioengineering > > >]
annual symposium of the IEEE EMBS Benelux Chapter
December 1st and 2nd 2011
Leuven and Brussels
[en] artificial organs ; implants
[en] Motor prostheses aim to restore functions lost to neurological disease and injury by translating neural signals into control signals for prosthetic limbs. Despite compelling proof of concept systems, barriers to clinical translation—mainly strict power dissipation constraints—still remain. The proposed solution is to use the ultra-low-power neuromorphic approach to potentially meet these constraints.
Won the 2nd best poster award price

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