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A bio-inspired coding (BIC) strategy for cochlear implants


Tabibi, Sonia; Kegel, Andrea; Lai, Wai Kong; Dillier, Norbert (2020). A bio-inspired coding (BIC) strategy for cochlear implants. Hearing Research, 388:107885.

Abstract

A bio-inspired coding (BIC) strategy was implemented in this study with the goal of better representation of spectral and temporal information. The auditory nerve fibers' (ANFs) characteristics such as refractory recovery, facilitation and spatial spread were obtained from ECAP data recorded in 11 CI recipients. These characteristics, together with a non-individualized model-derived adaptation effect, were integrated into the BIC strategy for a better selection of channels. Two variations of the BIC strategy were compared to the conventional advanced combination encoder (ACE) coding strategy: the BIC-I strategy based on the individual CI recipients' ECAP parameters, and the BIC-G strategy based on the median values of ECAP parameters from all CI recipients who participated in the study. The melodic contour identification (MCI) and Oldenburg sentence recognition in noise (OLSA) tests were used to assess and compare the three coding strategies. A significantly better performance in the transformed MCI test results with the rationalized arcsine transformation, was observed for both BIC strategy variations compared to the ACE strategy. There was no significant difference between the two variations of the BIC strategy and the ACE strategy in the OLSA test. No correlation was found between recovery time constants, absolute refractory periods, left and right width of SOE functions from three test electrodes and CI recipients' performances in the two experiments. However, significant correlations were found between facilitation time constant and amplitude and the results of the MCI and OLSA tests for the two variations of the BIC strategy.

Abstract

A bio-inspired coding (BIC) strategy was implemented in this study with the goal of better representation of spectral and temporal information. The auditory nerve fibers' (ANFs) characteristics such as refractory recovery, facilitation and spatial spread were obtained from ECAP data recorded in 11 CI recipients. These characteristics, together with a non-individualized model-derived adaptation effect, were integrated into the BIC strategy for a better selection of channels. Two variations of the BIC strategy were compared to the conventional advanced combination encoder (ACE) coding strategy: the BIC-I strategy based on the individual CI recipients' ECAP parameters, and the BIC-G strategy based on the median values of ECAP parameters from all CI recipients who participated in the study. The melodic contour identification (MCI) and Oldenburg sentence recognition in noise (OLSA) tests were used to assess and compare the three coding strategies. A significantly better performance in the transformed MCI test results with the rationalized arcsine transformation, was observed for both BIC strategy variations compared to the ACE strategy. There was no significant difference between the two variations of the BIC strategy and the ACE strategy in the OLSA test. No correlation was found between recovery time constants, absolute refractory periods, left and right width of SOE functions from three test electrodes and CI recipients' performances in the two experiments. However, significant correlations were found between facilitation time constant and amplitude and the results of the MCI and OLSA tests for the two variations of the BIC strategy.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Otorhinolaryngology
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:Sensory Systems
Language:English
Date:1 March 2020
Deposited On:11 Feb 2020 13:18
Last Modified:12 Feb 2020 04:16
Publisher:Elsevier
ISSN:0378-5955
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.heares.2020.107885
Related URLs:https://www.zora.uzh.ch/id/eprint/184363/
PubMed ID:32035288

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