2023
DOI: 10.1088/2057-1976/aceafb
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Investigating the electrode-electrolyte interface modelling in cochlear implants

Behnam Molaee-Ardekani,
Mary J Donahue

Abstract: Objective: Proposing a good electrode-electrolyte interface (EEI) model and properly identifying relevant parameters may help designing safer and more optimized auditory nerve fiber stimulation and recording in cochlear implants (CI). However, in the literature EEI model parameter values exhibit large variability. We aim to explain some root causes of this variability using the Cole model and its simpler form, the Basic RC model. Approach: We use temporal and spectral methods and fit the models to stimulation … Show more

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Cited by 3 publications
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“…This study aims to relate intracochlear voltages, EF spread and extracochlear currents predicted by a full-head model with previous modelling and experimental CI results. It must be noticed that our model does not consider the electrode contact impedances generated at the stimulation electrodes due to reactive components along the electrode-electrolyte interface (Paasche et al 2009, Kopsch et al 2022, Molaee-Ardekani and Donahue 2023, which would have changed the peak voltages predicted here. Normally, in TIM measures, these values show to be higher in the range of various units of kΩ (4-10 kΩ) (Cheng et al 2022, Hrncirik et al 2023.…”
Section: Model Validation Limitations and Future Workmentioning
confidence: 96%
“…This study aims to relate intracochlear voltages, EF spread and extracochlear currents predicted by a full-head model with previous modelling and experimental CI results. It must be noticed that our model does not consider the electrode contact impedances generated at the stimulation electrodes due to reactive components along the electrode-electrolyte interface (Paasche et al 2009, Kopsch et al 2022, Molaee-Ardekani and Donahue 2023, which would have changed the peak voltages predicted here. Normally, in TIM measures, these values show to be higher in the range of various units of kΩ (4-10 kΩ) (Cheng et al 2022, Hrncirik et al 2023.…”
Section: Model Validation Limitations and Future Workmentioning
confidence: 96%