An exemplary hearing evaluation system is configured to obtain a first auditory measurement dataset representative of one or more auditory measurements corresponding to a first ear of a user and that are acquired using a first auditory measurement test procedure having a first acoustic stimulus attribute set, obtain a second auditory measurement dataset representative of one or more auditory measurements corresponding to a second ear of the user and that are acquired using a second auditory measurement test procedure having a second acoustic stimulus attribute set different than the first acoustic stimulus attribute set, obtain a questionnaire response dataset representative of one or more responses to one or more question items associated with the user, and determine, based on the first auditory measurement dataset, the second auditory measurement dataset, and the questionnaire response dataset, a hearing profile of the user.

One embodiment of the present invention provides a method comprising running a monitoring agent on a connected electronic device, and determining, via the monitoring agent, a level of hearing impairment of an individual user associated with the connected electronic device. The method further comprises, in response to determining the individual user has some level of hearing impairment, selecting a notification mechanism suitable for notifying the individual user based on the level of hearing impairment, and invoking the monitoring agent to notify the individual user of an event in accordance with the notification mechanism selected.

An audiometric instrument that includes a dual pressure transducer configuration along a common air line with a first pressure transducer situated in a probe proximate to the ear of a user and a second pressure transducer situated proximate to a pressure control device. A restriction is preferably placed in the air line between the two pressure transducers to assist with obtaining a better comparison of the local pressure measurements from the different pressure transducers.

A fully autonomous system is used to diagnose an ear infection in a patient. For example, a processor receives patient data about a patient, the patient data comprising at least one of: patient history from medical records for the patient, one or more vitals measurements of the patient, and answers from the patient about the patient's condition. The processor receives a set of biomarker features extracted from measurement data taken from an ear of the patient. The processor synthesizes the patient data and the biomarker features into input data, and applies the synthesized input data to a trained diagnostic model, the diagnostic model comprising a machine learning model configured to output a probability-based diagnosis of an ear infection from the synthesized input data. The processor outputs the determined diagnosis from the diagnostic model. A service may then determine a therapy for the patient based on the determined diagnosis.

An alert is used to inform a user that their blood glucose level has dropped below a threshold (e.g., the user is hypoglycemic) or has increased above a threshold (e.g., the user is hyperglycemic). There is a hierarchy of alerts from lowest priority to highest priority. The alert is communicated by a user device (e.g., a mobile device), which is, for example, a smartphone, smart watch, home automation device, or the like. The alert is modified in order to increase the likelihood that the user receives or acknowledges the alert within a minimal amount of time. An intensity level (e.g., a volume) of an alert is modified based on, for example, whether the user has acknowledged a previous alert. A modality or a sensory channel of an alert is changed if an initial alert does fails to elicit a response from the user.

Disclosed are systems and methods for ambient sound enhancement on a mobile device. A user hearing profile is generated and a set of ambient sound enhancement digital signal processing (DSP) parameters is calculated for a sound enhancement algorithm, based at least in part on the user hearing profile. In response to a user initiating an ambient sound enhancement function on a mobile computing device, at least one set of calculated ambient sound enhancement DSP parameters is retrieved. Ambient sound is captured with a microphone of the mobile computing device and processed with an ambient sound enhancement DSP. The ambient sound enhancement DSP is parameterized with the retrieved set of calculated ambient sound enhancement DSP parameters and the DSP enhanced processed audio signal is outputted to a transducer of the mobile device.

Method for estimating a pure tone hearing threshold or a pure tone audiogram of a person with a non-calibrated audio-system, comprising the steps of performing a supra-threshold test at least over a portion of the audible frequency spectrum, wherein the audible frequency spectrum ranges particularly from 16 Hz to 20.000 Hz, wherein the supra-threshold test is performed on an unreferenced audio-system at a first relative sound level relative to a predefined output level of the unreferenced audio-system, determining the result of the supra-threshold test for at least a portion of the audible frequency spectrum, wherein the results of the supra-threshold test are provided particularly relative to the predefined output level of the unreferenced audio-system, determining from the progression of the determined result of the supra-threshold test at least one absolute pure tone threshold, wherein the at least one absolute pure tone threshold is provided in absolute physical units, particularly in decibels hearing level or decibels sound pressure level.

An auditory device assembly (1) comprises an earpiece (3) having an audio output device (7) for an ear (9) of a user and an audio processing unit (11, 33). The audio processing unit (11, 33) has a hearing-test mode and an audio streaming mode. In the hearing test mode the audio processing unit (11, 33) is arranged to determine at least one ear characteristic of the ear of the user based on at least one hearing test. In the audio streaming mode the audio processing unit (11, 33) is arranged to output an audio stream via the audio output device (7). The audio processing unit (11, 33) is arranged to adjust the output of the audio stream in the audio streaming mode based on the at least one ear characteristic determined in the hearing-test mode.

A audiological test system is provided for audiological testing of a patient situated at a test location, comprising a first display screen for monitoring of the audiological test system and that is positioned outside a viewing field of the patient when the patient is situated at the test location, a second display screen positioned within the viewing field of the patient when the patient is situated at the test location, a first switch located at the first display screen and adapted for control of the second display screen in such a way that predetermined information relating to operation of the audiological test system is not displayed on the second display screen upon activation of the first switch, and a second switch located at the second display screen and adapted for control of the second display screen in such a way that the predetermined information relating to operation of the audiological test system is displayed on the second display screen upon activation of the second switch.

Disclosed are systems and methods for user-dependent conditioning of stimuli in tests to elicit user responses to variations of one or more adaptive parameters of a user stimulus signal. The user stimulus signal is generated based on first and second adaptive parameters. The first adaptive parameter is modified to thereby generate a plurality of successive variations in the user stimulus signal, over one or more ranges of values of the second adaptive parameter. In response to modifying the first adaptive parameter, a plurality of user responses from a given user are received. Each user response indicates that one of the plurality of successive variations in the user stimulus signal has occurred. Based on an expected user response curve for the given user and a calculated time interval between successive user responses, an instantaneous rate of change for modifying the first adaptive parameter is adjusted such that the user responses are steered toward a neutral state around the expected user response curve.