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Lookup NU author(s): Dr Walid Al-Atabany, Dr Quoc Vuong, Dr Andrey Mokhov, Professor Patrick Degenaar
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
This work described a video information processing scheme for optogenetic forms of visual cortical prosthetics. Thearchitecture is designed to perform a processing sequence: Initially simplifying the scene, followed by a pragmaticvisual encoding scheme which assumes that initially optical stimulation will be stimulating bulk neural tissue ratherthan driving individual phosphenes. We demonstrate an optical encoder, combined with what we called a zero-RunLength Encoding (zRLE) video compression and decompression scheme – to wirelessly transfer information to animplantable unit in an efficient manner. In the final step, we have incorporated an even power distribution driver toprevent excessive power fluctuations in the optogenetic driving. The key novelty in this work centres on thecompleteness of the scheme, the new zRLE compression algorithm and our even power distributor. Furthermore,although the paper focusses on the algorithm, we confirm that it can be implemented on real time portable processinghardware which we will use for our visual prosthetics.
Author(s): Hou Z, Al-Atabany W, Farag R, Vuong QC, Mokhov A, Degenaar P
Publication type: Article
Publication status: Published
Journal: Journal of Neural Engineering
Year: 2020
Volume: 17
Issue: 5
Print publication date: 01/10/2020
Online publication date: 13/10/2020
Acceptance date: 29/06/2020
Date deposited: 30/07/2020
ISSN (print): 1741-2560
ISSN (electronic): 1741-2552
Publisher: Institute of Physics Publishing Ltd.
URL: https://doi.org/10.1088/1741-2552/abaf2e
DOI: 10.1088/1741-2552/abaf2e
PubMed id: 33055374
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