Abstract: Embodiments herein relate to ear-wearable devices and systems with features to track orthopedic issues and orthopedic procedure recovery. In an embodiment, an ear-wearable device is included having a control circuit, a microphone, and a sensor package. The ear-wearable device can be configured to receive an input regarding an occurrence of an orthopedic procedure, evaluate signals from the sensor package and/or the microphone, and determine a rehabilitative status of a device wearer with respect to the orthopedic procedure. Other embodiments are also included herein.

Abstract: Embodiments herein relate to a local assistant system responding to voice input using an ear-wearable device. The system detects a wake-up signal and receives a first voice input communicating a first query content. The system includes speech recognition circuitry to determine the first query content, speech generation circuitry, and an input database of locally-handled user inputs. If the first audio input matches one of the locally-handled user inputs, then the system takes a local responsive action. If the first audio input does not match one of the locally-handled user inputs, then the system transmits at least a portion of the first query content over a wireless network to a network resource.

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: A system and method of automatic transcription using a visual display device and an ear-wearable device. The system is configured to process an input audio signal at the display device to identify a first voice signal and a second voice signal from the input audio signal. A representation of the first voice signal and the second voice signal can be displayed on the display device and input can be received comprising the user selecting one of the first voice signal and the second voice signal as a selected voice signal. The system is configured to convert the selected voice signal to text data and display a transcript on the display device. The system can further generate an output signal sound at the first transducer of the ear-wearable device based on the input audio signal.

Abstract: Embodiments herein relate to a local assistant system responding to voice input using an ear-wearable device. The system detects a wake-up signal and receives a first voice input communicating a first query content. The system includes speech recognition circuitry to determine the first query content, speech generation circuitry, and an input database of locally-handled user inputs. If the first audio input matches one of the locally-handled user inputs, then the system takes a local responsive action. If the first audio input does not match one of the locally-handled user inputs, then the system transmits at least a portion of the first query content over a wireless network to a network resource.

Abstract: Embodiments herein relate to ear-wearable devices configured to detect aberrant patterns indicative of events related to the safety or health of a wearer and related methods. In a first aspect, an ear-wearable device is included having a control circuit, a microphone, a motion sensor, and a power supply. The ear-wearable device is configured to monitor signals from the microphone and/or the motion sensor to identify an aberrant pattern, and issue an alert when an aberrant pattern is detected. Other embodiments are also included herein.

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: A hearing assistance system and method are described herein. The system includes a first ear-worn device, a second ear-worn device, and a case. The system is configured to detect a vibration sequence at an IMU and decide whether to pair wireless communication devices of the first and second ear-worn devices based on the vibration sequence detected at the IMU.

Abstract: Disclosed herein, among other things, are systems, apparatus and methods for directional microphone accessories for hearing device applications. An apparatus includes a base, at least one strap configured to attach the base to a top portion of a seat back, and a pivoting mount configured to be attached to the base, the pivoting mount configured to hold a directional microphone assembly. The pivoting mount is further configured to maintain the directional microphone assembly in an approximately horizontal orientation independent of a recline angle of the seat back.

Abstract: A hearing assisting system is included having a first microphone and a second microphone. The system further includes a vision device having a display device, where the display device is configured to display visual information to the user when the user is wearing the vision device. The system is further configured to process audio signals to identify first audio content information and first audio direction information related to the first audio content information. The system further can transmit, to the vision device, first display information to cause the vision device to display a non-transcript content representation of the first audio content information and a direction representation of the first audio direction information using the display device.

Abstract: Embodiments herein relate to ear-wearable devices configured to detect patterns indicative of an occurrence, prodrome or sequelae of an anoxic or hypoxic neurological injury. In an embodiment, an ear-wearable device is included. The ear-wearable device can be configured to monitor signals from a microphone and/or a motion sensor to detect a pattern or patterns indicative of an occurrence of an anoxic or hypoxic neurological injury. In some embodiments, a method of monitoring an ear-wearable device wearer for an occurrence of an anoxic or hypoxic neurological injury is included. The method can include gathering signals from one or more of a microphone, a motion sensor, or another sensor of an ear-wearable device and monitoring the signals to detect a pattern or patterns indicative of an occurrence of an anoxic or hypoxic neurological injury. Other embodiments are also included herein.

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: Embodiments herein relate to systems, devices and methods for fitting hearing assistance devices. In a first aspect, a method of fitting a hearing assistance device is included, the method including providing an audio sample to a hearing assistance device wearer, receiving input from the hearing assistance device wearer regarding a preferred sound volume or perceived loudness, receiving input from the hearing assistance device wearer with the external device regarding a bass/treble balance, and determining a maximum power output of the hearing assistance device that does not exceed a loudness discomfort level (LDL). Other embodiments are also included herein.

Abstract: Embodiments herein relate to devices and related systems and methods for motion sickness prevention and mitigation. In an embodiment, a method of preventing or mitigating motion sickness in a subject is included, the method tracking motion of the subject using a first motion sensor; estimating a vestibular system input based on tracked motion of the subject; tracking head position of the subject using the first motion sensor; estimating a visual system input based on tracked head position of the subject; estimating consistency between the vestibular system input and the visual system input; and initiating a responsive measure if the estimated consistency crosses a threshold value. Other embodiments are also included herein.

Abstract: Embodiments herein relate to ear-wearable devices configured to administer therapy to individuals who have suffered anoxic or hypoxic neurological injury and/or assess recovery from such injuries and related systems and methods. In an embodiment, an ear-wearable device is included having a control circuit, a microphone, a motion sensor, and a power supply circuit, wherein the ear-wearable device is configured to initiate a therapy for a wearer of the ear-wearable device and monitor signals from the microphone and/or the motion sensor to detect execution of the therapy. In an embodiment, the ear-wearable device is configured to evaluate signals from at least one of the microphone and the motion sensor to assess recovery from an anoxic or hypoxic neurological injury. Other embodiments are also included herein.

Abstract: Embodiments herein relate to devices and related systems and methods for motion sickness prevention and mitigation. In an embodiment, a method of preventing or mitigating motion sickness in a subject is included, the method tracking motion of the subject using a first motion sensor; estimating a vestibular system input based on tracked motion of the subject; tracking head position of the subject using the first motion sensor; estimating a visual system input based on tracked head position of the subject; estimating consistency between the vestibular system input and the visual system input; and initiating a responsive measure if the estimated consistency crosses a threshold value. Other embodiments are also included herein.

Abstract: A system and method of automatic transcription using a visual display device and an ear-wearable device. The system is configured to process an input audio signal at the display device to identify a first voice signal and a second voice signal from the input audio signal. A representation of the first voice signal and the second voice signal can be displayed on the display device and input can be received comprising the user selecting one of the first voice signal and the second voice signal as a selected voice signal. The system is configured to convert the selected voice signal to text data and display a transcript on the display device. The system can further generate an output signal sound at the first transducer of the ear-wearable device based on the input audio signal.

Abstract: Embodiments herein relate to a local assistant system responding to voice input using an ear-wearable device. The system detects a wake-up signal and receives a first voice input communicating a first query content. The system includes speech recognition circuitry to determine the first query content, speech generation circuitry, and an input database of locally-handled user inputs. If the first audio input matches one of the locally-handled user inputs, then the system takes a local responsive action. If the first audio input does not match one of the locally-handled user inputs, then the system transmits at least a portion of the first query content over a wireless network to a network resource.

Abstract: A hearing assistance system and method are described herein. The system includes a first ear-worn device, a second ear-worn device, and a case. The system is configured to detect a vibration sequence at an IMU and decide whether to pair wireless communication devices of the first and second ear-worn devices based on the vibration sequence detected at the IMU.

Abstract: A system and method of automatic transcription using a visual display device and an ear-wearable device. The system is configured to process an input audio signal at the display device to identify a first voice signal and a second voice signal from the input audio signal. A representation of the first voice signal and the second voice signal can be displayed on the display device and input can be received comprising the user selecting one of the first voice signal and the second voice signal as a selected voice signal. The system is configured to convert the selected voice signal to text data and display a transcript on the display device. The system can further generate an output signal sound at the first transducer of the ear-wearable device based on the input audio signal.