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Updated: May 2, 2026

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
Published on: March 24, 2023
Single-Sided Deafness and Cochlear Implants: Performance in a Novel Combined Speech-in-Noise and Localization Task
Nadine I Ibrahim1, Obada Abdulrazzak, Chioma Anidi1
1Department of Otolaryngology-Head & Neck Surgery, University of Michigan, Ann Arbor, Michigan.
Objective:
This study aims to analyze the impact of single-sided deafness (SSD) on listening behavior to evaluate sound localization ability, speech-in-noise performance, and quantifying and comparing compensatory head movements in individuals with normal hearing (NH) and SSD, with and without a cochlear implant (CI).
Study Design:
Nonrandomized, prospective, human-subject study.
Setting:
Tertiary academic medical center.
Methods:
NH, SSD, and SSD-CI subjects were presented with Harvard IEEE sentences at varying target azimuths in a darkened, semi-anechoic chamber in background noise while head position was monitored. Head movement (total absolute head displacement, onset delay, and response time), localization accuracy, and speech-in-noise performance were analyzed.
Results:
SSD subjects demonstrated less accurate speech-in-noise and sound localization performance with a significant effect of hearing status and signal-to-noise ratio (SNR). Sound localization benefit with CI was limited and did not improve, with increasingly optimal SNR and speech-in-noise performance reaching the level of NH controls with more optimal SNR. Head movements varied with and without CI for total response time, whereby CI users had shortest response times. There was no difference between the SSD and SSD-CI conditions for onset delay and head displacement, despite significant differences compared with NH controls.
Conclusions:
Speech-in-noise performance may be the most significant improvement in CI use for SSD. Although sound localization abilities are present, there may be modest clinical significance. Head movement dynamics may highlight adaptive mechanisms that, if integrated into training or device programming, may further improve speech-in-noise and localization abilities.
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