A method for evaluating hearing of a user comprising: generating a baseline hearing profile for the user comprising a set of gain values based on a volume setting, each gain value in the set of gain values corresponding to a frequency band in a set of frequency bands; accessing a soundbite comprising a phrase characterized by a frequency spectrum predominantly within one frequency band; playing the soundbite amplified by a first gain in the frequency band; playing the soundbite amplified by a second gain in the frequency band; receiving a preference input representing a preference of the user from amongst the soundbite amplified by the first gain and the soundbite amplified by the second; and modifying a gain value, corresponding to the frequency band, in the baseline hearing profile based on the preference input to generate a refined hearing profile compensating for hearing deficiency of the user.

The present disclosure relates to compact hearing aids, components thereof, and support systems therefor, as well as methods of insertion and removal thereof. The compact hearing aids generally include a sensor, such as a microphone, an actuation mass, an energy source for providing power to the compact hearing aid, a processor, and an actuator enclosed in a housing that is designed to be inserted through the tympanic membrane during a minimally-invasive outpatient procedure. In operation, the microphone receives sound waves and converts the sound waves into electrical signals. A processor then modifies the electrical signals and provides the electrical signals to the actuator. The actuator converts the electrical signals into mechanical motion, which actuates the actuation mass to modulate the velocity or the position of the tympanic membrane.

A system, method and computer program are configured to interactively assist a user in evaluating and/or configuring a hearing aid. The system is equipped with a display element, with an input unit and with a processing unit. The environmental situations are shown on the display element. Based on a user input, a selected section of the environmental situation is determined and highlighted. A specific hearing situation is presented on the basis of the selection made by the user. An evaluation scale is displayed, allowing the user to enter a hearing value for a self-assessment of his hearing ability for the specific hearing situation, and the hearing value entered by the user is recorded. The above steps are repeated and hearing values are recorded for different specific hearing situations. Based on the hearing values entered by the user, setting values for the hearing aid are determined.

A method for determining social interaction of a user wearing a hearing device which comprises at least one microphone and at least one classifier. The method comprises: receiving an audio signal from the at least one microphone and/or a sensor signal from the at least one further sensor; identifying, by the at least one classifier, one or more predetermined user activity values by evaluating the audio signal from the at least one microphone and/or the sensor signal from the at least one further sensor; and calculating a user social interaction metric indicative of the social interaction of the user from the identified user activity values, wherein the user activity values are assigned to predefined social interaction levels, and wherein the user social interaction metric is a function of the user activity values weighted with their respective contribution to each of the social interaction levels.

Systems and methods may be used to determine a fit for a hearing assistance device shell model. For example, a method may include receiving an image of anatomy of a patient including at least a portion of a canal aperture of an ear of the patient, generating a patient model of a portion of the anatomy of the patient, the patient model indicating at least one of a height or width of the canal aperture, and determining, using the patient model, a best fit model from a set of hearing assistance device shell models generated using a machine learning technique. The method may include outputting an identification of the best fit model.

An own voice suppression apparatus applicable to a hearing aid is disclosed. The own voice suppression apparatus comprises: an air conduction sensor, an own voice indication module and a suppression module. The air conduction sensor is configured to generate an audio signal. The own voice indication module is configured to generate an indication signal according to at least one of user's mouth vibration information and user's voice feature vector comparison result. The suppression module coupled to the air conduction sensor and the own voice indication module is configured to generate an own-voice-suppressed signal according to the indication signal and the audio signal.

A method, comprising receiving at least one sound at an electronic device. The at least one sound is enhanced for the at least one user based on a compound metric. The compound metric is calculated using at least two sound metrics selected from an engineering metric, a perceptual metric, and a physiological metric. The engineering metric comprises a difference between an output signal and a desired signal. At least one of the perceptual metric and the physiological metric is based at least in part on input sensed from the at least one user in response to the received at least one sound.

The disclosed technology relates to a hearing system comprising a first hearing device configured for arrangement in an ear canal of a first ear of a user and a second hearing device configured for arrangement proximate to the first hearing device at the first ear of the user. The first hearing device and the second hearing device may each include a microphone, a signal processing unit, a loudspeaker, and a battery, such that both the first hearing device and the second hearing device are configured to function as a hearing device independently and when combined. In addition, the second hearing device may be configured to charge the battery of the first hearing device.

Presented herein are techniques to calculate long-term loudness measures for each of the prostheses in a bimodal hearing system and exchange this information across the two sides. The bimodal hearing system operates to ensure that the loudness differences between the two sides follow the ILDs between the two sides. Stated differently, the techniques presented herein determine a target loudness ratio based on the input signals (sound signals) received at each of the first second hearing prostheses in a bimodal hearing system. The techniques presented herein further determine an estimated inter-aural loudness ratio based on output signals that would be generated by each of the first and second hearing prostheses based on the input signals. Operation of either or both of the first or second hearing prostheses is adjusted so as to substantially match the estimated inter-aural loudness ratio to the target loudness ratio.

The present disclosure relates to compact hearing aids, components thereof, and support systems therefor, as well as methods of insertion and removal thereof. The compact hearing aids generally include a sensor, such as a microphone, an actuation mass, an energy source for providing power to the compact hearing aid, a processor, and an actuator enclosed in a housing that is designed to be inserted through the tympanic membrane during a minimally-invasive outpatient procedure. In operation, the microphone receives sound waves and converts the sound waves into electrical signals. A processor then modifies the electrical signals and provides the electrical signals to the actuator. The actuator converts the electrical signals into mechanical motion, which actuates the actuation mass to modulate the velocity or the position of the tympanic membrane.