Abstract: In one example, a method includes determining, by one or more processors of a hearing aid programmer, values for one or more properties of a first hearing aid; obtaining, by the one or more processors, based on feedback cancelation configurations of a plurality of other hearing aids having the same values for the one or more properties as the first hearing aid, a predicted initial feedback cancelation configuration for the first hearing aid; and programming, by the one or more processors, the first hearing aid based on the predicted initial feedback cancelation configuration.

Abstract: The present subject matter provides a hearing device with selective adjustment of processor settings based on various characteristics of an input sound, in response to adjustment of output sound volume by a user. This addresses problems of undesirable sound effects resulting from applying same changes to processor settings to input sounds of all levels, frequencies, and classes.

Abstract: Various embodiments of a predictive fall event management system and a method of using such system are disclosed. The system includes a body-worn device and a controller operatively connected to the body-worn device. The controller is adapted to receive physiological data representative of a physiological characteristic of a wearer of the body-worn device over a monitoring time period; receive contextual data representative of context information of the wearer over the monitoring time period; and determine one or more future physiological states or contextual states based at least in part on one or more of the physiological data and the contextual data. The controller is further adapted to determine, for a future time, whether a fall condition is satisfied based upon the one or more future physiological states or contextual states and generate a fall prevention output responsive to satisfaction of the fall condition.

Abstract: An ear-worn electronic device comprises a plurality of EEG sensors configured to sense EEG signals from or proximate a wearer's ear. At least one processor is configured to detect, during a baseline period of no wearer movement, EEG signals from the EEG sensors, and detect, during each of a plurality of candidate control movements by the wearer, EEG signals from the EEG sensors. The at least one processor is also configured to compute, using the EEG signals, discriminability metrics for the candidate control movements and the baseline period, the discriminability metrics indicating how discriminable neural signals associated with the candidate control movements and the baseline period are from one another. The at least one processor is further configured to select a subset of the candidate control movements using the discriminability metrics, each of the selected control movements defining a neural command for controlling the ear-worn electronic device by the wearer.

Abstract: 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.

Abstract: Disclosed is a multi-mode beam former, comprising a device for receiving a multi-mode input signal, and a device for constructing an optimization model and solving the optimization model to obtain a beam-forming weight coefficient for performing linear or non-linear combination on the multi-mode input signal. The optimization model comprises an optimization formula for obtaining the beam-forming weight coefficient. The optimization formula comprises: establishing an association between at least one electroencephalogram signal and a beam forming output, and optimizing the association to construct the beam-forming weight coefficient associated with the at least one electroencephalogram signal.

Abstract: A computing system comprising one or more electronic computing devices receives data from a hearing-assistance device. The computing system determines, based on the data received from the hearing-assistance device, a cognitive benefit measure for a wearer of the hearing-assistance device. The cognitive benefit measure being an indication of a change of a cognitive benefit of the wearer of the hearing-assistance device attributable to use of the hearing-assistance device by the wearer of the hearing-assistance device. The computing device outputs an indication of the cognitive benefit measure.

Abstract: A system may obtain a set of features characterizing a segment of inertial measurement unit (IMU) data generated by an IMU of an ear-wearable device. The system may apply a machine learning model (MLM) that takes the features characterizing the segment of the IMU data as input. The system may determine, based on output values produced by the MLM, whether a user of the ear-wearable device has potentially been subject to physical abuse. The system may then perform an action in response to determining that the user of the ear-wearable device has potentially been subject to physical abuse.

Abstract: Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

Abstract: A hearing device includes an enclosure comprising a shell and a faceplate and is configured for at least partial insertion within an ear of a user. An antenna structure of the hearing device is oriented such that a direction of an electric field (E-field) of a propagating electromagnetic signal generated by the antenna structure is directed non-tangentially with respect to the user at the location of the user's ear. The antenna structure includes an antenna disposed in or on the faceplate and a ground plane at least partially supported by the faceplate. A battery and electronic circuitry are disposed within the shell. The electronic circuitry is powered by the battery and is electrically coupled to send and/or receive signals via the antenna structure.

Abstract: A hearing aid assembly includes a receiver speaker enclosed within a receiver housing. The receiver housing defines a circuitous receiver acoustic channel, wherein the receiver channel defines an open side along at least a portion of the receiver channel. The receiver channel also defines a pass-through passage extending from a first side of the receiver housing to a second side of the receiver housing, wherein the pass-through passage is partially defined by the wall defining a receiver opening. The hearing aid assembly also includes an earbud configured to fit over at least a portion of the receiver housing and partially cover the open side of the receiver channel.

Abstract: A hearing device includes first, second, and third antennas oriented respectively along first, second, and third axes that are different from one another. The device includes first channel circuitry coupled to transceive and process antenna signals of each of the antennas. The antennas and the first channel circuitry communicate with another hearing device via a near field magnetic induction (NFMI) signal through a first near field magnetic induction (NFMI) communication channel. Second channel circuitry is coupled to transceive and process the antenna signals of each of the antennas. The antennas and the second channel circuitry communicate with the other device via the NFMI signal through a second NFMI communication channel. Third channel circuitry is coupled to transceive and process the antenna signals of each of the antennas. The antennas and the third channel circuitry communicate with the other device via the NFMI signal through a third NFMI communication channel.

Abstract: Disclosed herein, among other things, are apparatus and methods for a hearing assistance device with a sensor hub. Various aspects of the present subject matter include a method of using a hearing assistance device. A method includes sensing biometric signals from a wearer of a hearing assistance device using one or more sensor modules included in or on a receiver housing of the hearing assistance device, the receiver housing configured to connect to an end of a cable and configured to be placed in or near an ear canal of the wearer. The method also includes transmitting data indicative of the sensed biometric signals from the one or more sensor modules to a sensor hub in a connector of the cable, and processing the data using the sensor hub.

Abstract: A heart rate sensor within a hearing assistance device may provide heart rate information or other sensor data, which may be used to determine how well the hearing assistance device fits the patient's ear. The heart rate sensor data provides quantitative feedback that indicates how well the hearing assistance device fits the patient's ear. The heart rate sensor data may be used to provide an indication to the patient to reseat or otherwise adjust the fitting of the hearing assistance device. The improved fitting process provides the ability for the audiologist and patient to identify a preferred or optimized hearing assistance device geometry. This improved fit provides improved performance and reliability of the hearing assistance device.

Abstract: Embodiments herein relate to systems, devices and methods for managing pharmacological therapeutics and aspects of the same. In an embodiment, a hearing assistance device can include a control circuit, an electroacoustic transducer for generating sound in electrical communication with the control circuit, a power supply circuit in electrical communication with the control circuit, and a sensor package in electrical communication with the control circuit. The control circuit can be configured to evaluate a signal from at least one of the sensors of the sensor package to detect administration of a therapy or receive data indicating that administration of a therapy has taken place. The control circuit can also be configured to record an instance of a detected medication administration event along with a timestamp. Other embodiments are also included herein.

Abstract: Disclosed herein, among other things, are methods and apparatus for hearing assistance devices, and in particular to behind the ear and receiver in canal hearing aids with distributed processing. One aspect of the present subject matter relates to a hearing assistance device including hearing assistance electronics in a housing configured to be worn above or behind an ear of a wearer. The hearing assistance device includes an ear piece configured to be worn in the ear of the wearer and a processing component at the ear piece configured to perform functions in the ear piece and to communicate with the hearing assistance electronics, in various embodiments.

Abstract: A hearing assistance device adapted to be worn by a wearer comprises a processor configured to generate a sequence of audio cues that audibly guide the wearer through a series of actions involving the wearer's head and neck in accordance with a predetermined corrective or therapeutic maneuver. A speaker is configured to play back the sequence of audio cues for reception by the wearer. One or more sensors are configured to sense movement of the head during each of the actions. The processor is configured to determine if head movement for an action associated with each audio cue has been correctly executed by the wearer, and produce an output indicative of successful or unsuccessful execution of the actions by the wearer.

Abstract: Secondary path measurements and associated acoustic transducer-to-eardrum responses are obtained from test subjects. Both a least squares estimate and a reduced dimensionality estimate are determined that both estimate a relative transfer function between the secondary path measurements and the associated acoustic transducer-to-eardrum responses. An individual secondary path measurement for a user is performed based on a test signal transmitted via a hearing device into an ear canal of the user. An individual cutoff frequency for the individual secondary path measurement is determined. First and second acoustic transducer-to-eardrum responses below and above the cutoff frequency are determined using the individual secondary path measurement and the least squares estimate. A sound pressure level at an eardrum of the user can be predicted using the first and second receiver-to-eardrum responses.

Abstract: A hearing device for electrically coupling to skin of a user includes a body having a housing forming at least part of an outer surface. The device includes an acoustic transducer and an electrode disposed at least partially in the body. The electrode includes an outer conductor disposed at least partially in the housing and an inner conductor electrically coupled to the outer conductor and disposed subflush to the outer surface. A method of forming the hearing device includes providing a cast shell, forming an elastomeric conductor in a cavity of the cast shell, and removing a thin outer wall of the cast shell to form the housing of the hearing device.

Abstract: Disclosed herein, among other things, are systems and methods for a user adjustment interface using remote computing resources. Specifically, a system can include a mobile device in communication with a hearing assistance device or a remote server. The mobile device can interpret an acoustic environment and send information about the environment to a remote server. The remote server can determine and send information to the mobile device for use in a user interface. The mobile device can receive a user selection of hearing assistance parameter information to be sent to the hearing assistance device.