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: This disclosure describes a method comprising: obtaining, by a processing system that includes one or more processors implemented in circuitry, a signal from a magnetic sensor of a hearing instrument; determining, by the processing system, a context of the hearing instrument based at least in part on the signal from the telecoil; and initiating, by the processing system, one or more actions based on the context of the hearing instrument.

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: 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: A processing system obtain signals that are generated by or generated based on sensors that are included in one or more hearing instruments. Additionally, the processing system determine, based on the signals, whether a posture of a user of the hearing instruments is a target posture. The processing system generate information based on the posture of the user.

Abstract: An example system includes an ear-wearable device comprising a housing and a rechargeable battery located within the housing; a supplemental power storage device configured to provide electrical energy; and circuitry configured to transfer, responsive to occurrence of an event, electrical energy from the supplemental power storage device to the rechargeable battery prior to an initial use of the ear-wearable device.

Abstract: A wellness evaluation system may determine, based on data generated by a first set of sensors powered by one or more batteries of one or more ear-wearable devices, that a user of the one or more ear-wearable devices is currently in an environment that includes human-directed communication signals. If so, a second set of sensors may be activated such that the one or more batteries provides an increased amount of power to the second set of sensors. Furthermore, the wellness evaluation system may determine based on data generated by the second set of sensors, whether the user has satisfied a target level of a wellness measure. If the user has not satisfied the target level of the wellness measure, the wellness evaluation system may perform an action to encourage the user to perform one or more activities to increase an achieved level of the wellness measure.

Abstract: An example method includes capturing, via one or more sensors of a computing system, a representation of an ear of a user; determining, based on the representation, a value of a measurement of the ear of the user; and selecting, based on the value of the measurement, a length of a wire or tube of a hearing instrument to be worn on the ear of the user.

Abstract: A wellness evaluation system may determine, based on data generated by a first set of sensors powered by one or more batteries of one or more ear-wearable devices, that a user of the one or more ear-wearable devices is currently in an environment that includes human-directed communication signals. If so, a second set of sensors may be activated such that the one or more batteries provides an increased amount of power to the second set of sensors. Furthermore, the wellness evaluation system may determine based on data generated by the second set of sensors, whether the user has satisfied a target level of a wellness measure. If the user has not satisfied the target level of the wellness measure, the wellness evaluation system may perform an action to encourage the user to perform one or more activities to increase an achieved level of the wellness 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: A wellness evaluation system may determine, based on data generated by a first set of sensors powered by one or more batteries of one or more ear-wearable devices, that a user of the one or more ear-wearable devices is currently in an environment that includes human-directed communication signals. If so, a second set of sensors may be activated such that the one or more batteries provides an increased amount of power to the second set of sensors. Furthermore, the wellness evaluation system may determine based on data generated by the second set of sensors, whether the user has satisfied a target level of a wellness measure. If the user has not satisfied the target level of the wellness measure, the wellness evaluation system may perform an action to encourage the user to perform one or more activities to increase an achieved level of the wellness measure.