Self-guided Parameter Fitting for Cochlear Implant Users (2014-2015)

A cochlear implant is a surgically-implanted electronic device that converts sound into an electrical signal in the brain of a person who is hard-of-hearing. The complexity of the system as well as confounding factors such as brain plasticity and changing physiology require that the parameters associated with the cochlear implant be continually updated to maximize listening performance and user satisfaction. Updating the parameters of these devices currently requires visits to a clinician, which limits the number and scope of updates possible within a fixed time frame. As a solution, design and development of a take-home fitting software system would enable implant users to interact with and control their personal device’s parameters. Cochlear implant users support the development of such a product and are comfortable adjusting their own device parameters; however, the ideal method by which to guide users to optimize their device parameters without clinician interaction is unknown.

This project developed a graphical user interface (GUI) that guides cochlear implant users to adjust their device parameters so that their speech recognition and listening satisfaction are improved. Taking a modular approach, the team added parameters for optimization to the GUI one at a time, starting with the parameters known to have the greatest impact on listening outcomes and moving into parameters having more subtle effects. Team members coded the GUI components and tested them with human subjects. Components were adapted based on the test results.


Summer 2014 – Spring 2015

Team Outcomes

Graphical User Interface for Self-Guided Frequency Allocation in Cochlear Implants (honors thesis by Vinay Nagaraj)

Self-guided Parameter Fitting for Cochlear Implant Users (poster by M. Fikret Yalcinbas, Vinay Nagaraj, Kedar Prabhudesai, Leslie M. Collins, Chandra S. Throckmorton)


Vinay Ragaraj ‘16

This Team in the News

Hacking into a Bionic Ear

Vinay Nagaraj: My Bass Connections Pathway

Being a part of this project team was invaluable in learning about research and lab work. I’m currently trying to write a thesis within the realm of this project as applied to my major in Mechanical Engineering to graduate with distinction. –Vinay Nagaraj

Team Leaders

  • Lawrence Appelbaum, School of Medicine-Psychiatry and Behavioral Sciences
  • Kevin Caves, School of Medicine-Head and Neck Surgery and Communication Sciences
  • Leslie Collins, Pratt School of Engineering-Electrical & Computer Engineering
  • Chandra Throckmorton, Pratt School of Engineering-Electrical & Computer Engineering
  • Sara Unrein, School of Medicine-Surgery

/undergraduate Team Members

  • Kristen Bailey, Neuroscience (BS)
  • Vinay Nagaraj, Mechanical Engineering (BSE)
  • Muhammed Yalcinbas, Biomedical Engineering (BSE)