A method performed by an electronic hearing device with an earpiece configured to be worn in an ear, includes: engaging a hearing mode wherein a compensated output signal is based on current hearing compensation data. Performing a first fitting procedure including: obtaining first hearing compensation data via audiometric measurements; emitting an otoacoustic stimulation signal and capturing an acoustic signal including otoacoustic emissions. In response to receiving a first input signal, performing a first monitoring procedure including: emitting an otoacoustic stimulation signal and capturing an acoustic signal including otoacoustic emissions, if any. Determining a deviation value based on the second acoustic signal and the third acoustic signal; and determining whether the deviation value satisfies a first criterion. In accordance with a determination that the deviation value satisfies the first criterion, communicating a first notification signal indicative of the deviation from the hearing device.

The use of the correct, required length of a cable in a hearing aid substantially contributes to the wearing comfort of the hearing aid. At least one ear depiction of an ear is created by a camera. An associated ear geometry is determined on the basis of the ear depiction. The required length of the cable for the hearing aid can in turn be determined by use of the ear geometry.

Presented herein are techniques for assessing one or more outcomes associated with implantation of one or more electrodes into the inner ear of a recipient.

A method for compensating hearing deficiencies with a hearing device includes receiving a sound signal; attenuating an output sound pressure level of the sound signal dependent on an input sound pressure level of the sound signal; and outputting the attenuated sound signal with a loudspeaker of the hearing device; wherein the output sound pressure level is attenuated, when the input sound pressure level is above an upper speech recognition kneepoint of a user, which upper speech recognition kneepoint is stored in the hearing device and which has been selected dependent on a sound pressure level dependent speech recognition ability of the user.

In accordance with some embodiments, systems, methods and media for automatically determining audio gain profiles for fitting personal audio output devices are provided. In some embodiments, a method for automatically determining audio gain profiles comprises: determining hearing thresholds; determining gain profiles based on the hearing thresholds generating augmented audio signals using the gain profiles; causing the augmented audio signals to be presented using a speaker of an output device; receiving a rating associated with each gain profile; determining fitness values based on the ratings; generating a new generation of gain profiles based on the fitness values, each gain profile comprising bits representing the set of gain values; augmenting the new generation of gain profiles by exchanging a string of bits from a first gain profile with a corresponding string of bits from a second gain profile; and outputting a final gain profile to the output device.

Systems and methods are provided for customizing an auditory prosthesis or other medical device. Customizing the auditory prosthesis includes obtaining and evaluating system data. The system data includes data from multiple sensors, including one or more sensors of an auditory prosthesis and one or more sensors of a recipient computing device. Based on the evaluation of the system data, a target behavior is determined, such as operating the auditory prosthesis in a particular sonic environment or with particular auditory prosthesis settings.

A method processes an initial audio signal, having a target portion and a side portion, by receiving of the initial audio signal; modifying the received initial audio signal using a first signal modifier to obtain a first modified audio signal and modifying the received initial audio signal using a second signal modifier to obtain a second modified audio signal; comparing received initial audio signal with the first modified audio signal to obtain a first perceptual similarity value describing the perceptual similarity between the initial audio signal and the first modified audio signal; and comparing the received initial audio signal with the second modified audio signal to obtain a second perceptual similarity value describing the perceptual similarity between the initial audio signal and the second modified audio signal; and selecting the first or second modified audio signal dependent on the respective first or second perceptual similarity value.

A hearing normalization and correction system and process provides accurate correction for users with mild to moderate hearing loss by using actual measured hearing response at multiple sound pressure levels. User measured hearing data is collected at considerably higher resolution and accuracy at multiple sound pressure levels and is automatically converted to multiple accurate correction responses. Dynamic adaptive cross-fade response correction is used to deliver hearing normalization at varying sound pressure levels. Adaptive release response allows the hearing normalization system to accurately track the envelope of the incoming audio signal providing greatly enhanced accuracy and transparency. Adaptive headroom control is also applied to increase both input and output headroom providing professional dynamic range performance. The hearing normalization and correction system delivers audio fidelity and performance transcending that of normal hearing aid technology.

At least one exemplary embodiment is directed to a method of generating a hearing impairment compensation function to process audio reproduced by an earphone device. The compensation function includes processing the audio to compensate for frequency sensitivity to improve speech intelligibility.

Disclosed is a system and method for individualized hearing aid prescription which consists of a test procedure that enables the fitting of an individualized estimation of the SII model to individual listeners efficiently and an optimization process which translates the resulting individualized model to the prescribed gains across frequencies for programming into the user's hearing aids. The test involves the recognition of one or more words presented in background noise, which better approximates the daily listening experiences of hearing-aid users compared to the pure-tone detection in a silent environment task which is commonly utilized during conventional audiometric testing. In the estimated SII model, five parameters describe in a custom fashion the relative weights of speech information across the five frequency bands for a given listener. The results from the speech test is used to determine the desirable amount of gain for each frequency region to optimize the user's aided speech intelligibility. The resulting gains for the individual may then be programmatically applied to the individual's prescribed hearing aid device(s).