Detecting and identifying a predetermined health event can include detecting a potential occurrence of the predetermined health event for a user by processing in real-time motion signals corresponding to motion of the user. A likelihood that the potential occurrence is an actual occurrence of the predetermined health event can be determined based on template matching of the motion signals. In response to determining that the likelihood exceeds a predetermined threshold, audio signals coinciding in time with the motion of the user can be processed using one or more layers of a multilayered audio event classifier.

The disclosure relates to a brain stimulation system (102), comprising: a) a computer program product, e.g. a data carrier, preferably a non-transitory data carrier, or a data stream, comprising program code (P1, P1a) which, when loaded and executed on an electronic control unit (108), provides an operation control system, or b) an electronic control unit (108) with a program code (P1, P1a) loaded on the electronic control unit (108), wherein the program code (P1, P1a), when executed on the electronic control unit (108), provides an operation control system (200), wherein the operation control system (200) is configured to control a brain training and/or stimulation session for a brain, and wherein the operation control system (200) comprises a plurality of control system functionalities, the control system functionalities comprising:

a stimulation functionality (202) which is configured to cause the electronic control unit (108) to issue a stimulation command to an electrical brain stimulation device (122) to cause the electrical brain stimulation device (122) to perform an electrical brain stimulation procedure; and

a presentation functionality (204) which is configured to cause the electronic control unit (108) to issue a presentation command in order to present a task to be performed by a user (120) on a user interface (110), wherein preferably the stimulation functionality (202) and the presentation functionality (204) are linked (254 to 262) or linkable to one another.

Examples disclosed herein are relevant to monitoring and treating sensory conditions affecting an individual. Sensors and intelligence integrated within a sensory prosthesis (e.g., an auditory prosthesis) can automatically obtain objective data regarding the ability of one or more of an individuals senses during day-to-day activities. A treatment action can be taken based on the objective data. Further disclosed herein are techniques relating to reducing the gathering of irrelevant sensory input and automatically transmitting relevant data to a caregiver device.

In some embodiments, a method of creating an automatic language characteristic recognition system. The method can include receiving a plurality of audio recordings. The method also can include segmenting each of the plurality of audio recordings to create a plurality of audio segments for each audio recording. The method additionally can include clustering each audio segment of the plurality of audio segments according to audio characteristics of each audio segment to form a plurality of audio segment clusters. Other embodiments are provided.

A method includes obtaining, by a processor, a score quantifying an estimated degree to which an instance of an articulatory event-type indicates a state, with respect to a disease, in which the instance was produced. The method further includes, using the score, facilitating, by the processor, a computer-implemented procedure for evaluating the state of a subject based on a test utterance produced by the subject. Other embodiments are also described.

A method of predicting mental state includes extracting image data, audio data, and semantic text data from video data, where the video data portrays a first individual. The method further includes analyzing the image data to identify a first feature set, analyzing the audio data to identify a second feature set, analyzing the semantic text data to identify a third feature set, and predicting a mental state for the individual based on the first feature set, the second feature set, the third feature set, and a multidimensional mental state model. The predicted mental state is output. The multidimensional mental state model includes a first dimension, a second dimension, and a third dimension. The first dimension corresponds to a first aspect of mental state, the second dimension corresponds to a second aspect of mental state, and the third dimension corresponds to a third aspect of mental state.

Hat, helmet, and other headgear apparatus includes dry electrophysiological electrodes and, optionally, other physiological and/or environmental sensors to measure signals such as ECG from the head of a subject. Methods of use of such apparatus to provide fitness, health, or other measured or derived, estimated, or predicted metrics are also disclosed.

The present invention may include a computer receives one or more communications and data from a sensor. The computer determines an activity of a user based on the received data, wherein the activity is determined by a trained neural network. The computer calculates a stress coefficient based on the activity and the data. The computer generates a cognitive notifications choreographer model from the stress coefficient and one or more communications and causes a communication software to reply to the one or more communications based on the cognitive notifications choreographer model determining the stress coefficient above a threshold value.

The technology described herein is generally directed towards collecting digital twin datasets from individual users to represent their individual physical, emotional, chemical and/or environmental conditions. A user's digital twin is matched to one or more other digital twins with similar physical, emotional, chemical, and/or environmental conditions. The matched digital twins can share data and learnings via a virtual anonymous relationship. Multiple digital twins that represent users with similar conditions may be found and treated collectively as a group; a user via his or her digital twin can poll the group to receive and process responses from each respondent. A digital twin can be a therapist or a researcher who emulates a patient and uses the emulated digital twin as a proxy to monitor and process the results of other digital twins.

A body worn or implantable hearing prosthesis, including a device configured to capture an audio environment of a recipient and evoke a hearing percept based at least in part on the captured audio environment, wherein the hearing prosthesis is configured to identify, based on the captured audio environment, one or more biomarkers present in the audio environment indicative of the recipient's ability to hear.