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Proceedings Paper

A predictive model for artificial mechanical cochlea
Author(s): Riaz U. Ahmed; Afifa Adiba; Sourav Banerjee
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Paper Abstract

To recover the hearing deficiency, cochlea implantation is essential if the inner ear is damaged. Existing implantable cochlea is an electronic device, usually placed outside the ear to receive sound from environment, convert into electric impulses and send to auditory nerve bypassing the damaged cochlea. However, due to growing demand researchers are interested in fabricating artificial mechanical cochlea to overcome the limitations of electronic cochlea. Only a hand full number of research have been published in last couple of years showing fabrication of basilar membrane mimicking the cochlear operations. Basilar membrane plays the most important role in a human cochlea by responding only on sonic frequencies using its varying material properties from basal to apical end. Only few sonic frequencies have been sensed with the proposed models; however no process was discussed on how the frequency selectivity of the models can be improved to sense the entire sonic frequency range. Thus, we argue that a predictive model is the missing-link and is the utmost necessity. Hence, in this study, we intend to develop a multi-scale predictive model for basilar membrane such that sensing potential of the artificial cochlea can be designed and tuned predictively by altering the model parameters.

Paper Details

Date Published: 26 March 2015
PDF: 7 pages
Proc. SPIE 9429, Bioinspiration, Biomimetics, and Bioreplication 2015, 94290K (26 March 2015); doi: 10.1117/12.2084769
Show Author Affiliations
Riaz U. Ahmed, Univ. of South Carolina (United States)
Afifa Adiba, Ohio State Univ. (United States)
Sourav Banerjee, Univ. of South Carolina (United States)

Published in SPIE Proceedings Vol. 9429:
Bioinspiration, Biomimetics, and Bioreplication 2015
Akhlesh Lakhtakia; Mato Knez; Raúl J. Martín-Palma, Editor(s)

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