In some embodiments, the present disclosure provides an exemplary technically improved system and method for controlling the body movements and facial expressions of a digital character in real time by using: a body-motion capture system comprising a headset configured to be worn on a head of a user and comprising controllers and sensors that can be used to track at least one head or body motion of the user (including arms and hands); and correspondingly control at least one head or body motion (including arms and hands) of a digital character in real time based, at least in part, on the captured motion data; a mobile computing device configured to track and capture facial expression data relating to at least one facial expression of the user, and use at least that data to correspondingly control at least one facial expression of the digital character in real time; a microphone configured to capture an audio output of the user, and control an audio output of the digital character in real-time based, at least in part, on the captured audio output; an integration computing device configured to integrate the audio output, the motion data and the facial expression data to control the audio output, the motion, and the facial expression of the digital character; a vest configured to be worn on an body of the user and a structural member attached to the vest and configured to hold the mobile computing device at a predetermined distance from a face of the user so that the mobile computing device can track and capture the at least one facial expression of the user.

The present invention relates to a waterproof and trackable hearing aid that can be worn during swimming, bathing, diving and other water activities. The hearing aid is paired with a software application using a wireless channel and can be tracked when lost or goes out of Bluetooth range. The device includes rubber protection for prevention from physical damage and water. A small charging and suction case is used for charging the hearing aid and removing moisture from the hearing aid. The hearing aid is filter-less and can provide amplified sounds to the tympanic membrane of the wearer. The hearing aid includes a solar panel for providing power to the hearing aid device, and can be used for taking calls and listening to music.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user's voice, storing the user's voice in a memory of an earpiece device, or storing the user's voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

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.

A method and system for heterogeneous event detection. Sensor data is obtained and divided into discrete data windows. Each data window is defined by and corresponds to a time period of the sensor data. A time-frequency representation over the time period is calculated for each data window. A filter mask is calculated based on the data window corresponding to the time-frequency representation. The filter mask is applied for reverting the time-frequency representation to a time representation, resulting in filtered data. Features, such as extrema or other inflection points, are identified in the filtered data. The features define events, and transforming the time-frequency representation back into the time domain emphasizes differences between more and less prominent frequencies, facilitating identification of heterogeneous events. The method and system may be applied to body movements of people or animals, automaton movement, audio signals, light intensity, or any suitable time-dependent variable.

Examples of the disclosure describe systems and methods for estimating acoustic properties of an environment. In an example method, a first audio signal is received via a microphone of a wearable head device. An envelope of the first audio signal is determined, and a first reverberation time is estimated based on the envelope of the first audio signal. A difference between the first reverberation time and a second reverberation time is determined. A change in the environment is determined based on the difference between the first reverberation time and the second reverberation time. A second audio signal is presented via a speaker of a wearable head device, wherein the second audio signal is based on the second reverberation time.

A method for performing voice dictation with an earpiece worn by a user includes receiving as input to the earpiece voice sound information from the user at one or more microphones of the earpiece, receiving as input to the earpiece user control information from one or more sensors within the earpiece independent from the one or more microphones of the earpiece, inserting a machine-generated transcription of the voice sound information from the user into a user input area associated with an application executing on a computing device and manipulating the application executing on the computing device based on the user control information.

In some embodiments, a system comprises a host computing device and an audio device communicatively coupled to the host device and including at least one speaker and a plurality of light emitters. The host computing device can include a processor(s) and one or more machine-readable, non-transitory storage mediums with instructions configured to cause the processor(s) of the host computing device to perform operations including receiving user environment data by one or more sensors of the host computing device, receiving user selection data corresponding to a selected mode of operation of the audio device, determining a characterization profile of a surrounding environment of the user based on the user environment data, and sending the characterization profile to the audio device, the characterization profile configured to cause the audio device to control the plurality of light emitters based on the characterization profile and the selected mode of operation.

The present invention is directed to a wearable system wherein elements of the system, including various sensors adapted to detect biometric and other data and/or to deliver drugs, are positioned proximal to, on the ear or in the ear canal of a person. In embodiments of the invention, elements of the system are positioned on the ear or in the ear canal for extended periods of time. For example, an element of the system may be positioned on the tympanic membrane of a user and left there overnight, for multiple days, months, or years. Because of the position and longevity of the system elements in the ear canal, the present invention has many advantages over prior wearable biometric and drug delivery devices.

A method of incorporating environmental acoustic sources into a virtual environment by measuring real environment acoustic sources and locations and incorporating them into a virtual environment with virtual acoustic sources.