Hearing loss affects a very large portion of the general population. According to WHO more than 5 % of the world’s population suffer from hearing impairment to a degree that is considered to be disabling. The largest proportion of hearing impairment in the population is due to permanent sensorineural hearing loss associated with the aging process. With the increase in life expectancy, permanent age-related sensorineural hearing loss will be progressively more prevalent in the future.
Hearing impaired subjects potentially benefit from using hearing aids, since these compensate for the decrease in hearing sensitivity. To work optimally, it is, however, crucial that the hearing instrument is configured in close accordance with the hearing abilities of the individual user. This is traditionally done in the clinic based on behavioural tests such as pure tone audiometry and speech discrimination testing, which provide information on the degree and nature of the hearing loss. Further, auditory perception is optimized through adaption of the audio processing (i.e. the directionality, noise reduction and compression) of the hearing aid according to the interchanging auditory scene of the user. This is done automatically by the hearing aid based on the acoustical input, but moreover, the user may be able to switch between a number of different settings such as “directional/omnidirectional” or “speech/music/TV” to modify the audio processing and thereby output of the hearing aid. Still, getting additional and more detailed information about the actual sound perception and mental state of the user would be of great advantage for the hearing aid as it would allow the audio processing to be even more tailored to the specific situation. Thus, the performance of hearing aids could potentially be enhanced if they were able to obtain feedback about the auditory perception from the auditory system of the user directly.
Ear-EEG is an EEG recording approach where, the EEG is recorded from electrodes embedded in a personalized hearing aid-like earpiece placed in the ear canal (Figure 1). Since the ear-EEG methodology provides a non-invasive, discrete and unobtrusive way of measuring EEG signals, it has great potential for use in the clinic as well as in everyday life and could potentially be integrated into future hearing aids.
Initial investigations suggest that well established auditory evoked potentials, such as the auditory steady-state response (ASSR) and the P1-N1-P2 complex can be observed from the ear-EEG advocating for the general application of ear-EEG in audiometric characterization of human hearing. The feasibility of such an application has further been evaluated in a recent comparative study of hearing threshold estimation based on ASSR using both ear-EEG and conventional scalp EEG recordings in a controlled laboratory setting. There, it was found, that hearing threshold levels can be estimated from ear-EEG recordings with a precision comparable to that of conventional scalp EEG. The study, however, also suggests that the ear-EEG platform is challenged by lower signal-to-noise ratios when measured in-ear (both measuring and reference electrode in the same ear) than found in scalp-EEG. Thus, a lower performance, measured as the fraction of established thresholds, was found for ear-EEG than for scalp EEG. Overall, the study supports the feasibility of ear-EEG in hearing threshold level estimation as well as more general applications of the ear-EEG platform in audiometric characterization of the human hearing. Still, it also underlines the necessity of optimization through further investigation and characterization of the fundamental properties of ear-EEG. This is even more important if the technology is to be used outside the controlled environment of the laboratory in everyday life applications such as hearing aids, which are subjected to high degrees of non-stationary noise during daily use. Moreover, a pilot study using high-density earpieces (15 electrodes in each ear) indicate that the ASSR amplitude-phase topography may vary relatively much across the ear. The study supports the potential for the ear-EEG platform, but underlines that the use of the right electrode configuration is crucial to obtain a good signal-to-noise ratio in the ear-EEG recordings.
The aim of the project is to determine the presence and spatial distribution of auditory responses in ear-EEG recordings through high-density measurements.
The project is funded by the William Demant Foundation grant number 17-0726 and WS Audiology.
