Abstract: Embodiments herein relate to ear-wearable device systems with features to monitor dental health. In an embodiment, an ear-wearable device system is included having an ear-wearable device. The ear-wearable device can include a microphone and a sensor package. The sensor package can include a motion sensor. The ear-wearable device system can be configured to evaluate signals from at least one of the microphone and the motion sensor to detect an occurrence of a dental health condition. In some embodiments, an ear-wearable device system herein can be configured to compare signals from at least one of a microphone and a motion sensor from a time period prior to a dental procedure with signals from a time period after the dental procedure. In some embodiments the ear-wearable device system is configured to evaluate signals a sensor to detect an occurrence of a dental hygiene event. Other embodiments are also included herein.

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: One or more processing circuits may obtain context information associated with a user of one or more hearing instruments, wherein the context information is based on a first set of sensor data generated by a plurality of sensors of the one or more hearing instruments and a second set of sensor data generated by a plurality of sensors of a computing device communicatively coupled to the one or more hearing instruments. The one or more processing circuits may determine, based on at least a portion of the context information, an auditory intent of the user for a given auditory context. The one or more processing circuits may associate the auditory intent with one or more actions, such as actions to adjust one or more settings of the one or more hearing instruments. The one or more processing circuits may invoke the one or more actions associated with the auditory intent.

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 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.