Dual-Stage Algorithm to Identify Channels with Poor Electrode-to-Neuron Interface in Cochlear Implant Users
Document Type
Conference Proceeding
Publication Date
5-18-2016
Journal / Book Title
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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
