161
Views
0
CrossRef citations to date
0
Altmetric
Articles

Modeling and simulation of cochlear perimodiolar electrode based on composite spring-mass model

, , &
Pages 290-297 | Received 19 Jan 2021, Accepted 28 Jun 2021, Published online: 15 Jul 2021
 

Abstract

This paper proposes, a method for the physical modeling of the perimodiolar electrode, particularly for the process of recovering its preset shape with the guide wire drawn out, based on the composite spring-mass model by employing the virtual-volumetric spring inspired from the traditional spring-mass model. Simulation experiments of modeling and virtual insertion of perimodiolar electrode were carried out. The results indicated that the mean and standard deviation of the difference between the local deformation angles of the simulated and measured sets of mass points, (1, 2, 3), (2, 3, 4), …, (13, 14, 15), were 6.34° and 5.98°, respectively. Additionally, the physical model of the perimodiolar electrode can reflect the overall morphological changes of the real perimodiolar electrode.

Acknowledgement(s)

The authors would like to thank Cochlear Ltd for providing the perimodiolar electrode array and also thank Eye & ENT Hospital of Fudan University for providing the cochlea specimen and technical support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study was financed by the National Natural Science Foundation of China (51705493).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.