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Updated: May 6, 2026

Cortical Source Analysis of High-Density EEG Recordings in Children
Published on: June 30, 2014
The speech reception threshold can be estimated using EEG electrodes in and around the ear
Heidi Bliddal Borges1,2, Johannes Zaar1,3, Emina Alickovic1,4
1Eriksholm Research Centre, Oticon A/S, DK-3070 Snekkersten, Denmark.
None:
Objective.Previous studies have demonstrated that the speech reception threshold (SRT) can be estimated using scalp electroencephalography (EEG), referred to as SRTneuro. The present study assesses the feasibility of using ear-EEG, which allows for discreet measurement of neural activity from in and around the ear, to estimate the SRTneuro.Approach.Twenty young normal-hearing participants listened to audiobook excerpts at varying signal-to-noise ratios (SNRs) whilst wearing a 66-channel EEG cap and 12 ear-EEG electrodes. A linear decoder was trained on different electrode configurations to estimate the envelope of the audio excerpts from the EEG recordings. The reconstruction accuracy was determined by calculating the Pearson's correlation between the actual and the estimated envelope. A sigmoid function was then fitted to the reconstruction-accuracy-vs-SNR data points, with the midpoint of the sigmoid serving as the SRTneuroestimate for each participant.Main results.Using only in-ear electrodes, the estimated SRTneurowas within 3 dB of the behaviorally measured SRT (SRTbeh) for 6 out of 20 participants (30%). With electrodes placed both in and around the ear, the SRTneurowas within 3 dB of the SRTbehfor 19 out of 20 participants (95%) and thus on par with the reference estimate obtained from full-scalp EEG. Using only electrodes in and around the ear from the right side of the head, the SRTneuroremained within 3 dB of the SRTbehfor 19 out of 20 participants.Significance.These findings suggest that the SRTneurocan be reliably estimated using ear-EEG, especially when combining in-ear electrodes and around-the-ear electrodes. Such an estimate can be highly useful e.g. for continuously adjusting noise-reduction algorithms in hearing aids or for logging the SRT in the user's natural environment.
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