Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/94623
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Type: Conference paper
Title: Information theoretic optimization of cochlear implant electrode usage probabilities
Author: Gao, X.
Grayden, D.
McDonnell, M.
Citation: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013, vol.2013, pp.5974-5977
Publisher: IEEE
Issue Date: 2013
Series/Report no.: IEEE Engineering in Medicine and Biology Society Conference Proceedings
ISBN: 9781457702167
ISSN: 1557-170X
2694-0604
Conference Name: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013) (3 Jul 2013 - 7 Jul 2013 : Osaka, Japan)
Statement of
Responsibility: 
Xiao Gao, David B. Grayden, Mark D. McDonnell
Abstract: Cochlear implants are neural prostheses that can restore hearing. Contemporary cochlear implant devices consist of up to 22 electrodes. An open question for future cochlear implants is whether new electrode designs that enable less current spread may provide improved hearing performance through more precise control of neural activation, more electrodes, or more precise positioning. Here we use a recently proposed information theoretic model for the electro-neural interface that enables estimates to be made of the optimal number of electrodes for different amounts of current spread. We apply information theoretic approaches for finding the channel capacity in the model to enable estimates of optimal electrode usage probabilities and positions. We also compare the performance in the model when auditory nerve fibers are assumed to be heterogenous, with a random distribution of firing thresholds and relative spreads, versus an assumption that they are all identical.
Keywords: Cochlea
Humans
Cochlear Implantation
Probability
Electrodes, Implanted
Cochlear Implants
Hearing
Models, Theoretical
Rights: Copyright status unknown
DOI: 10.1109/EMBC.2013.6610913
Grant ID: http://purl.org/au-research/grants/arc/DP1093425
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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