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Inferring the stability of LIFE through brain-machine interfaces

DiGiovanna, J and Citi, L and Yoshida, K and Carpaneto, J and Principe, JC and Sanchez, JC and Micera, S (2008) 'Inferring the stability of LIFE through brain-machine interfaces.' Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology". 2008 - 2011.

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Abstract

We examine neural signals from Longitudinally implanted Intra-Fascicular Electrodes (LIFE) in a chronic, rabbit model. Translation-invariant wavelet de-noising methods are used to improve SNR. Then traditional template-based spike sorting is applied to discriminate single units. We investigate the effect of discriminating between identified units on Brain Machine Interface (BMI) decoding performance. We infer the stability of LIFE based on decoding performance with and without current BMI methods to counter-act electrode neural signal degradation. © 2008 IEEE.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 13 Mar 2014 10:10
Last Modified: 05 Feb 2019 19:15
URI: http://repository.essex.ac.uk/id/eprint/8811

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