CC BY-NC-ND 4.0 · Laryngorhinootologie 2021; 100(S 02): S227
DOI: 10.1055/s-0041-1728462
Abstracts
Otology / Neurotology / Audiology

Utilizing an EEG recording system for measuring cochlear microphonics

F Schertenleib
1   Universitätsklinik für Hals-Nasen-Ohren-Heilkunde, Evangelisches Krankenhaus, Carl von Ossietzky-Universität, Oldenburg
› Author Affiliations
 

The outer hair cells (OHC) of the cochlea play an important role in generating neural responses in the inner ear. Electrodes placed near the cochlea can be used to measure the electrical activity of the OHC - called cochlear microphonics (CM). Unlike the coded neural response of the cochlea to higher brain areas, CMs seem to reflect the original auditory stimulus. The amplitude of this signal might serve as an indicator for preserved hair cell activity. Clinical devices for the measurement of early acoustic potentials enable the detection of CMs. However, these systems have numerous practical limitations in terms of epoch length, selectable stimuli, sampling rate and access to raw data, making them unsuitable for scientific applications.

Based on an EEG recording system, our setup allows the recording of epochs of any length, at 19.2kHz sampling rate. Stimuli are generated by a custom-made software and are simultaneously presented with a trigger signal. Thus, any acoustic signal can be used as a stimulus. In addition, the system enables processing of real-time data, e.g. during surgical procedures. For the analysis of the raw data we use functions from the EEGLAB toolbox in MATLAB. Using a tympanic membrane (TM) electrode, we were able to measure CMs in four participants in response to tone bursts with frequencies 500 Hz up to 8 kHz.

With growing interest in CMs in the field of cochlear implantation our measurement setup provides valuable data that could contribute to developing clinical applications and instruments in the future.

Poster-PDF A-1447.pdf



Publication History

Article published online:
13 May 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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