A machine-implemented method for automated detection of drowsiness, which includes receiving from an imaging device directed at the face of an operator a series of images of the face of the operator onto processing hardware, on the processor detecting facial landmarks of the operator from the series of images to determine the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator, on the processor detecting the facial pose of the operator from the series of images to determine the level of gaze fixation by the operator, on the processor calculating the level of drowsiness of the operator by ensembling the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator and the level of gaze fixation by the operator, and generating an alarm when the calculated level of drowsiness of the operator exceeds a predefined value.

Described herein are methods, devices, systems, software, and platforms used to evaluate individuals such as children for behavioral disorders, developmental delays, and neurologic impairments. Specifically, described herein are methods, devices, systems, software, and platforms that are used to analyze video and/or audio recordings of individuals having one or more behavioral disorders, developmental delays, and neurologic impairments.

A computer system for determining onset of an acute coronary syndrome (ACS) event in a remote computing environment comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories is provided. The stored program instructions include capturing, using a camera, a first image at a first time of an iris and a pupil of a first eye of a user; following the capturing of the first image, identifying in the first image a first iris information; capturing, using the camera, a second image at a second time of the iris and the pupil of the first eye of the user; following the capturing of the second image, identifying in the second image a second iris information; determining whether the first iris information is within an allowable range of the second iris information; and providing an indication of a likely ACS event based on a determination of whether the first iris information is within the allowable range of the second iris information.

Described herein is a method (800) and system for controlling one or more illumination devices in an eye tracker system (100) such that a measured pupil/iris contrast exceeds a predefined minimum pupil/iris contrast. The method (100) includes: a. capturing images of a subject (102), including one or both of the subject's eyes, during predefined image capture periods; b. illuminating, from one or more illumination devices (108 and 110), one or both of the subject's eyes during the predefined image capture periods, wherein at least one illumination device (108 and 110) is located sufficiently close to a lens of the camera to generate bright pupil effects; and c. selectively varying the output power of at least one of the illumination devices (108 and 110) to generate a bright pupil reflection intensity such that a measured pupil/iris contrast in a captured image exceeds a predefined minimum pupil/iris contrast.

Methods and systems for assessing autism spectrum disorder (ASD) are described herein. Data identifying one or more behaviors associated with ASD may be received. A scenario specifying a plurality of different tasks may be received. An extended reality (XR) device may present and XR environment to a subject. The XR device may present, in the XR environment, a first task of the plurality of different tasks. Based on a subject interaction with one or more objects in the XR environment, interaction data may be calculated. Based on the interaction data, at least one second task may be selected from the plurality of different tasks. The at least one second task may be configured to train a different skill as compared to the first task. The XR environment may be modified to present the second task.

This drowsiness estimating device estimates a subject's drowsiness from a time-series signal of the subject's eye-openness width. A filtering circuitry filters the time-series signal of the eye-openness width to eliminate signal changes due to the subject blanking and outputs the filtered time-series signal of eye-openness. A feature calculator calculates a feature from at least the filtered time-series signal of the eye-openness width. A drowsiness estimator estimates a drowsiness evaluated value from the feature and outputs an estimated result. The feature calculator includes at least a first feature calculation circuit that calculates a variation of the filtered time-series signal of the eye-openness width within a feature calculation window width and outputs the variation as a first feature.

A system for controlling blood pressure includes a wearable interface having an internal contact surface, the wearable interface configured to at least partially encircle a first portion of a first limb of a subject, a sensing module carried by the wearable interface and configured to determine at least a change in blood pressure of the first limb of the subject, and an energy application module carried by the wearable interface and configured to apply energy of two or more types to the first limb of the subject.

Apparatus, systems, and methods are provided for generating a quantified indicator of cognitive skills in an individual. In certain configurations, the apparatus, systems, and methods can be implemented for enhancing cognitive skills in an individual.

The present disclosure relates to a method and a system for detecting a neurological disease and an eye gaze-pattern abnormality related to the neurological disease of a user. The method comprises displaying stimulus videos on a screen of an electronic device and simultaneously filming with a camera of the electronic device to generate a video of the user's face for each one of the stimulus videos, each one of the stimulus videos corresponding to a task. The method further comprises providing a machine learning model for gaze predictions, generating the gaze predictions for each video frame of the recorded video, and determining features for each task to detect the neurological disease using a pre-trained machine learning model.

A medical rehabilitation device for clinically rehabilitating individuals suffering from medical conditions affecting the vestibular ocular system, and other neurocognitive functions. The rehabilitation device includes a support base having an elongate slot, and a plurality of arms adjustably attached to the support base via the elongated slot, where each arm includes a magnetic strip for selectively positioning visual targets thereon to solicit patient recognition of colors and positions of the visual targets during both vestibular ocular reflex, and other neurocognitive exercises. Each arm and the support base includes measurement markings extending along the top longitudinal surface of each arm adjacent the magnetic strips and along the elongate slot, respectively, to provide measured and objective charted indicators for vestibular ocular reflex and other neurocognitive functions over time. The arms are adjustable in horizontal, vertical, and diagonal positions to selectively adjust the difficulty of the exercises in a plane of vision.