A hearing aid is described which incorporates an antenna integrated into the housing that is configured to radiate with linear polarization such that the electric field is perpendicular to the head of a wearer. The described technique results in lower propagation losses from ear to ear and an improvement in ear-to-ear communications using a far-field link (e.g., in the 2.4 GHz band).

The present invention is directed to a hearing aid which includes a lateral ear canal assembly and a medial ear canal assembly. In embodiments of the invention the medial ear canal assembly may include smart circuitry adapted to control parameters and outputs of the medial ear canal assembly. In embodiments of the invention various methods and circuitry are described, wherein the methods and circuitry are adapted to improve the performance and efficiency of the hearing aid.

An exemplary hearing device is configured to concurrently maintain a first link with a source and a second link with a second hearing device. The hearing device scans, while not receiving data via the first link, the second link for a preamble of a binaural data packet for a first time period. Based on whether the preamble is detected, the hearing device selectively: receives the binaural data packet and ignores the first link while receiving the binaural data packet if the preamble of the binaural data packet is detected during he first time period; and scans the first link for a preamble of a data packet for a second time period if the preamble of the binaural data packet is not detected during the first time period.

A hearing aid has at least two input transducers and at least one output transducer. The input transducers generate an input signal from a sound signal from the surroundings. At least two directional signals with different directional characteristics are formed from the input signals and the directional signals are examined for the presence of a useful signal. A first weighting factor is assigned to the directional signal with the largest signal component of the useful signal and a second weighting factor is assigned to the other directional signals. The directional signals are multiplied by the respectively assigned weighting factor, and an output signal is then formed from the multiplication result. The output signal is converted into a sound signal by the output transducer.

Embodiments herein relate to hearing assistance devices that can control other devices based on hearing assistance device events and/or status. In an embodiment, a hearing assistance system includes a hearing assistance device that can include a control circuit, a microphone in electrical communication with the control circuit, an electroacoustic transducer for generating sound in electrical communication with the control circuit, and a power supply circuit. The hearing assistance device can be configured to initiate sending a hearing accommodative command to a separate controllable device upon occurrence of a hearing assistance device event. The hearing assistance device event can be raised by detection of at least one of the hearing assistance device not being worn by the subject, the hearing assistance device in a not-in-use operating state, the hearing assistance device entering a recharging mode, and the hearing assistance device entering a shut-down sequence. Other embodiments are also included herein.

A method (600) of operating a binaural ear level audio system in order to improve speech intelligibility and a binaural ear level audio system adapted to carry out said method.

A method of defining and setting a nonlinear signal processing of a hearing device, e.g. a hearing aid, by machine learning is provided. The hearing device being configured to be worn by a user at or in an ear or to be fully or partially implanted in the head at an ear of the user, the method comprising providing at least one electric input signal representing at least one input sound signal from an environment of a hearing device user, determining a normal-hearing representation of said at least one electric input signal based on a normal-hearing auditory model, determining a hearing-impaired representation of said at least one electric input signal based on a hearing-impaired auditory model, determining optimised training parameters by machine learning, where determining optimised training parameters comprises iteratively adjusting the training parameters, and comparing the normal-hearing representation with the hearing-impaired representation to determine a degree of matching between the normal-hearing representation and the hearing-impaired representation, until the degree of matching fulfils predetermined requirements, and, when the degree of matching fulfils the predetermined requirements, determining corresponding signal processing parameters of the hearing device based on the optimised training parameters. A hearing device is further provided.

The present disclosure relates to a method of creating a trusted bond between a hearing device and a user accessory device, wherein the method comprises: transmitting, by a hearing device fitting system, an authentication key to the hearing device; creating, by the hearing device fitting system authentication data comprising the authentication key in encrypted form; obtaining, by the user accessory device, the created authentication data; receiving, by the user accessory device, identification information from the hearing device the identification information identifying the hearing device; decrypting, by the user accessory device, the encrypted authentication key comprised in the obtained authentication data using at least the received identification information; establishing communication between the hearing device and the user accessory device based on the authentication key.

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.

A charger for charging an audio-device-accumulator of an audio device which is wearable on a head of a user and contains an interface for the transfer of electrical energy to the audio-device-accumulator. The charger contains an energy source configured as a hybrid battery for supplying the interface in a first charging mode. The hybrid battery contains a charger-accumulator and a fuel cell.