This disclosure relates to systems and methods for remote diagnostic medical testing. Some embodiments relate to resource allocation. Some embodiments relate to dynamic resource allocation. In some embodiments, a method for remote diagnostic testing can include receiving a request to begin a testing session, selecting at least one guidance provision scheme from a plurality of guidance provision schemes, beginning the testing session using the selected at least one guidance provision scheme, receiving data indicative of one or more characteristics of the testing session, determining to modify the testing session for the user, and altering the testing session. In some embodiments a method can include determining, based on data indicative of the user's sentiment, one or more baseline scores associated with one or more emotion and detecting a change in the user sentiment during the testing session.

Technologies are provided for remote neuropsychological assessments and other types of remote assessments (medical or otherwise).

Systems and methods for assisting user with hearing by amplifying sound using an amplifier with gain and amplitude controls for a plurality of frequencies; and applying a learning machine to identify an aural environment and adjust the amplifiers for optimum hearing.

The disclosed technology generally relates to a hearing device configured to adjust its settings when it detects the hearing device user is experiencing stress related to the hearing device applying a processing scheme. The hearing device can use vital signs of the hearing device user to determine whether a user is stressed. The hearing device can also determine whether the user has become stressed as a result of applied setting or an applied processing scheme of the hearing device based on a change in the vital sign of the hearing device user. The disclosed technology also includes a method for reducing stressing when using a hearing device.

This document discusses, among other things, systems and methods for managing pain in a subject. A system may include one or more sensors configured to sense from the subject information corresponding to emotional reaction to pain, such as emotional expression. The emotional expression includes facial or vocal expression. A pain analyzer circuit may generate a pain score using signal metrics of facial or vocal expression extracted from the sensed information. The pain score may be output to a user or a process. The system may additionally include a neurostimulator that can adaptively control the delivery of pain therapy by automatically adjusting stimulation parameters based on the pain score.

Aspects relate to systems and methods for determining actor status according to behavioral phenomena. An exemplary system includes an eye sensor configured to detect an eye parameter as a function of an eye phenomenon, a speech sensor configured to detect a speech parameter as a function of a speech phenomenon, and a processor in communication with the eye sensor and the speech sensor; the processor is configured to receive the eye parameter and the speech parameter, determine an eye pattern as a function of the eye parameter, determine a speech pattern as a function of the speech parameter, and correlate one or more of the eye pattern and the speech pattern to a cognitive status.

A method for monitoring feeding maturation in premature babies, the method including measuring an acoustic response from a baby during a selected time period to provide acoustic information; comparing the measured acoustic response against a train data set to determine an indication of a swallow event; and measuring a respiration pattern of the baby during a swallow cycle using a peak and valley model to provide respiration data, where a feeding maturity of the baby is determinable in dependence on the swallow indication and respiration data.

The present disclosure provides acoustic and natural language processing (NLP) models for predicting whether a subject has a behavioral or mental health state of interest based at least in part on input speech from said subject.

A method includes providing one or more instructions to perform a first action associated with administration of a medication; obtaining first data representing a capture of a patient performing the first action based on the one or more instructions; extracting information about movements of the patient from the first data; presenting an image configured to induce an emotional response in the patient; obtaining second data representing capture of the patient performing one or more microexpressions within 250 milliseconds of presentation of the image; obtaining additional data including one or more of demographic information of the patient, information of a disease associated with the patient, or one or more characteristics of the medication; and based on the extracted information about the movements, the one or more microexpressions, and the additional data, determining a medical outcome including a progression of the disease in the patient.

System and method for detecting cognitive decline in a subject using a classification system for detecting cognitive decline in the subject based on a speech sample. The classification system is trained using speech data corresponding to audio recordings of speech from normal and cognitive decline patients to generate an ensemble classifier comprising a plurality of component classifiers and an ensemble module. Each of the plurality of component classifiers is a machine-learning classifier configured to generate a component output identifying a sample data as corresponding to a normal patient or a cognitive patient. The machine-learning classifier is generated based on a subset of available features. The ensemble module receives component outputs from all of the component classifiers and generates an ensemble output identifying the sample data as corresponding to a normal or cognitive decline patient based on the component outputs.