Title

Dual-Stage Algorithm to Identify Channels with Poor Electrode-to-Neuron Interface in Cochlear Implant Users

Authors

Stefano Cosentino, Medical Research Council
Lindsay De Vries, University of Washington
Rachel Scheperle, St. Louis Children's HospitalFollow
Julie Bierer, University of WashingtonFollow
Robert Carlyon, Medical Research Council

Document Type

Conference Proceeding

Publication Date

5-18-2016

Abstract

Users of cochlear implants rely on a number of electrodes to perceive acoustic information. The extent to which their hearing is restored depends on a number of factors including the electrode-to-neuron interface. We describe an approach to detect instances of poor-performing channels based on physiological data known as electrically evoked compound action potentials (ECAPs). The proposed approach - termed Panoramic ECAP («PECAP») - combines nonlinear optimization stages with different constraints to recover neural activation patterns for all electrodes. Data were obtained from nine cochlear implant subjects and used to run the PECAP tool to identify possible instances of poor-performing channels. Data from one subject revealed a shifted peak («dead region»).

DOI

10.1109/ICASSP.2016.7471792

Montclair State University Digital Commons Citation

Cosentino, Stefano; Vries, Lindsay De; Scheperle, Rachel; Bierer, Julie; and Carlyon, Robert, "Dual-Stage Algorithm to Identify Channels with Poor Electrode-to-Neuron Interface in Cochlear Implant Users" (2016). Department of Communication Sciences and Disorders Faculty Scholarship and Creative Works. 32.
https://digitalcommons.montclair.edu/communcsci-disorders-facpubs/32