Abstract: Disclosed herein, among other things, are systems and methods for active noise cancellation (ANC) for hearing device applications. A method includes measuring a receiver-to-inward-facing microphone response during an in-situ calibration stage for the hearing device, estimating a receiver-to-eardrum transfer function using the measured receiver-to-inward-facing microphone response, and measuring an outward-facing microphone to inward-facing microphone transfer function for an external noise sound field during run-time operation of the hearing device.

Abstract: Disclosed herein, among other things, are systems and methods for active noise cancellation (ANC) for hearing device applications. A method includes estimating a first sound pressure on an ear drum of a wearer of the hearing device caused by a hearing processing signal, estimating a second sound pressure on the ear drum of the wearer of the hearing device caused by a leakage path of the hearing device, and computing a ratio of the first sound pressure and the second sound pressure to predict a comb-filtering effect for the hearing device. The method also includes computing an ANC controller using the computed ratio in one or more frequency ranges, and canceling leaked sound into an ear canal of the wearer for the hearing device in the one or more frequency ranges using the ANC controller.

Abstract: A method comprises determining, based on signals from sensors of hearing instruments, current values of context parameters; determining, based on the current values of the context parameters, that a current context of the hearing instruments has changed or is likely to change from a first to a second context of a plurality of contexts, wherein each of the contexts corresponds to a different unique combination of potential values of the context parameters; updating statistics of the contexts, wherein for each of the contexts, the statistics of the context include statistics with respect to time the hearing instruments spent in the context; and based on the determination that the current context of the hearing instruments has changed or is likely to change from the first context to the second context, initiating, based on the statistics of at least one of the first or second contexts, one or more actions.

Abstract: An ear-worn electronic device comprises a microphone arrangement configured to sense sound in an acoustic environment, an acoustic transducer, and a non-volatile memory configured to store parameter value sets each associated with a different acoustic environment, at least one of which is associated with an acoustic environment with muffled speech. A control input of the device is configured to receive a control input signal produced by a user-actuatable control, a sensor or an external electronic device. A processor is configured to classify the acoustic environment as one with muffled speech using the sensed sound and, in response to a signal received from the control input, apply one or more of the parameter value sets appropriate for the classification to enhance intelligibility of muffled speech.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: Embodiments herein relate to ear-wearable systems and devices that can detect respiratory conditions and related parameters. In an embodiment, an ear-wearable device for respiratory monitoring is included having a control circuit, a microphone, and a sensor package. The ear-wearable device can be configured to analyze signals from the microphone and/or the sensor package and detect a respiratory condition and/or parameter based on analysis of the signals. In an embodiment, an ear-wearable system for respiratory monitoring is included having an accessory device and an ear-wearable device. In an embodiment, a method of detecting respiratory conditions and/or parameters with an ear-wearable device system is included. Other embodiments are also included herein.

Abstract: An ear-worn electronic device comprises at least one microphone configured to sense sound in an acoustic environment, an acoustic transducer, and a non-volatile memory configured to store a plurality of parameter value sets, each of the parameter value sets associated with a different acoustic environment. A control input is configured to receive a control input signal produced by at least one of a user-actuatable control of the ear-worn electronic device and an external electronic device communicatively coupled to the ear-worn electronic device in response to a user action. A processor is operably coupled to the microphone, the acoustic transducer, the non-volatile memory, and the control input. The processor is configured to classify the acoustic environment using the sensed sound and apply, in response to the control input signal, one of the parameter value sets appropriate for the classification.

Abstract: In an audio signal, one or more processing circuits recognize spoken content in a user's own speech signal using speech recognition and natural language understanding. The spoken content describes a listening difficulty of the user. The one or more processing circuits generate, based on the spoken content, one or more actions for hearing devices and feedback for the user. The one or more actions attempt to resolve the listening difficulty. Additionally, the one or more processing circuits convert the user feedback to verbal feedback using speech synthesis and transmit the one or more actions and the verbal feedback to the hearing devices via a body-worn device. The hearing devices are configured to perform the one or more actions and play back the verbal feedback to the user.

Abstract: An ear-worn electronic device comprises a microphone configured to sense sound in an acoustic environment, an acoustic transducer, and a non-volatile memory configured to store a plurality of parameter value sets, each of the parameter value sets associated with a different acoustic environment. A control input is configured to receive a control input signal produced by at least one of a user-actuatable control of the ear-worn electronic device and an external electronic device communicatively coupled to the ear-worn electronic device in response to a user action. A processor is configured to classify the acoustic environment using the sensed sound and determine a listening intent preference of the user. The processor is configured to apply, in response to the control input signal, one of the parameter value sets appropriate for the classification and the listening intent preference of the user.

Abstract: Various embodiments of a monitoring system are disclosed. The monitoring system includes first and second sensors each adapted to detect a characteristic of a subject of the system and generate data representative of the characteristic of the subject, and a controller operatively connected to the first and second sensors. The controller is adapted to receive data representative of first and second characteristics of the subject from the first and second sensors, and determine statistics for first and second condition substates of the subject over a monitoring time period based upon the data received from the first and second sensors. The controller is further adapted to compare the statistics of the first and second condition substates, confirm the first condition substate if it is substantially similar to the second condition substate, and determine the statistics of an overall condition state of the subject based upon the confirmed first condition substate.

Abstract: In an audio signal, one or more processing circuits recognize spoken content in a user's own speech signal using speech recognition and natural language understanding. The spoken content describes a listening difficulty of the user. The one or more processing circuits generate, based on the spoken content, one or more actions for hearing devices and feedback for the user. The one or more actions attempt to resolve the listening difficulty. Additionally, the one or more processing circuits convert the user feedback to verbal feedback using speech synthesis and transmit the one or more actions and the verbal feedback to the hearing devices via a body-worn device. The hearing devices are configured to perform the one or more actions and play back the verbal feedback to the user.

Abstract: Embodiments herein relate to systems, devices and methods for the treatment of equilibrium disorders and improving gait and balance. In an embodiment, a method of treating an equilibrium disorder is included. The method can include monitoring device wearer movement with a movement sensor, identifying a movement pattern consistent with an equilibrium disorder, estimating characteristics of the equilibrium disorder, and applying stimulation to at least one of the right ear, left ear, or brainstem of the device wearer of an ear-worn device. Other embodiments are also included herein.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A hearing aid includes a sound classification module to classify environmental sound sensed by a microphone. The sound classification module executes an advanced sound classification algorithm. The hearing aid then processes the sound according to the classification.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A set of one or more processing circuits obtains eye movement-related eardrum oscillation (EMREO)-related measurements from one or more EMREO sensors of a hearing instrument. The EMREO sensors are located in an ear canal of a user of the hearing instrument and are configured to detect environmental signals of EMREOs of an eardrum of the user of the hearing instrument. The one or more processing circuits may perform an action based on the EMREO-related measurements.

Abstract: A hearing aid includes a sound classification module to classify environmental sound sensed by a microphone. The sound classification module executes an advanced sound classification algorithm. The hearing aid then processes the sound according to the classification.

Abstract: In an audio signal, one or more processing circuits recognize spoken content in a user's own speech signal using speech recognition and natural language understanding. The spoken content describes a listening difficulty of the user. The one or more processing circuits generate, based on the spoken content, one or more actions for hearing devices and feedback for the user. The one or more actions attempt to resolve the listening difficulty. Additionally, the one or more processing circuits convert the user feedback to verbal feedback using speech synthesis and transmit the one or more actions and the verbal feedback to the hearing devices via a body-worn device. The hearing devices are configured to perform the one or more actions and play back the verbal feedback to the user.

Abstract: Disclosed herein, among other things, are apparatus and methods for noise characterization and attenuation for hearing assistance devices. In various embodiments, a method of operating a hearing assistance device includes receiving an audio signal using a microphone of the hearing assistance device and identifying a transient in the audio signal. Linear predictive coding (LPC) is used to isolate speech segments and non-speech segments of the transient and fluctuating noise, and the non-speech segments of the transient and fluctuating noise are attenuated to reduce annoyance of the noise and maintain audibility of perceptually important transients in speech.

Abstract: The signal processing functions of a hearing aid as described above necessarily cause some delay between the time the audio signal is received by the microphone or wireless receiver and the time that the audio is actually produced by the output transducer. In some situations, signal processing incorporating longer delays may be better able to improve signal-to-noise ratio (SNR) or other functional parameters for a hearing aid wearer, but a balance should be struck between these positive effects of delay and other negative effects. The techniques described herein address the problem of balancing the positive and negative effects of delay.