Systems and methods for detecting onset, presence, and progression of particular states, including intoxication, include observing eye movements of a subject and correlating the observed movements to known baseline neurophysiological indicators of intoxication. A detection system may record eye movement data from a user, compare the eye movement data to a data model comprising threshold eye movement data samples, and from the comparison make a determination whether or not intoxication or impairment is present. The detection system may alert the user to take corrective action if onset or presence of a dangerous condition is detected. The eye movements detected include saccadic and intersaccadic parameters such as intersaccadic drift velocity. Measurements may be collected in situ with a field testing device. An interactive application may be provided on a user device to provoke the desired eye movements during recording.

A processing subsystem generates perceived images from information bearing nerve impulses that are transmitted from a subject's eye(s) to a visual processing region of the subject's brain along one or more nerves in response to the subject viewing a real-world scene. The processing subsystem generates display images based on the perceived images, and controls a display device to display the display images to the subject. In certain embodiments, the processing subsystem generates the display images by manipulating or modifying the perceived images to include virtual images, and provides a type of virtual pointing on the display images that is used to invoke one or more actions.

Vision-based stimulus monitoring and response systems and methods are presented, wherein detection, via image(s) of a patient through an external stimulus, such as a caregiver, prompts analysis of the response of the patient, via secondary patient sensors or via analysis of patient image(s), to determine an autonomic nervous system (ANS) state.

A reinforcement learning (RL) based adaptive state observation model usable for implementing a brain machine interface (BMI) is proposed for decoding a brain signal to determine a movement action and controlling a machine to perform the movement action. In the model, the brain signal is processed by a neural network (NN) for applying a nonlinear mapping defined by NN weights to the brain signal to thereby yield a transformed brain signal. The NN learns the nonlinear mapping by RL, allowing the weights to be adaptively and continuously updated to follow nonlinearity and non-stationarity of the brain signal. The transformed brain signal is processed by a Kalman filter (KF) to yield a control signal for controlling the machine to perform the movement action, thereby utilizing the KF to provide smooth generation of the control signal while blocking adverse influence of nonlinearity and non-stationarity of the brain signal to the KF.

A system to perform remote oculography includes light-occluding goggles configured to be worn by a patient. The light-occluding goggles include an infrared camera positioned to capture one or more first images of a first eye of the patient. The light-occluding goggles also include a display positioned such that it is viewable by a second eye of the patient. The display is configured to display a pattern for the patient to view. The light-occluding goggles also include a sensor configured to detect information regarding a position of a head of the patient. The system also includes a visible light camera configured to capture one or more second images of the patient as the patient wears the light-occluding goggles.

A method and apparatus for quantifying differences in human sensorimotor performance useful for diagnosing, assessing, and/or detecting brain injury and/or a neurological disorder, or identifying exceptional performance in a subject. In a task a subject's limb movement is restricted to a limited workspace and an object moves towards the limb. The objective of the task is for the subject to contact the object with the limb within a set time period. During the task a perturbation directed to the object and/or limb, or other feature of the environment, may occur on some trials, requiring a rapid motor correction in order to contact the object, or the subject may receive an alternative instruction on whether to interact with the object. Position data and/or motion data and/or kinetic data of the limb or portions thereof with respect to a presented object are obtained, and a data set is acquired for a plurality of trials. The acquired data set provides information about brain injury and/or a neurological disorder in the subject or exceptional capabilities of the subject.

A system for monitoring patients during a consciousness-altering therapeutic treatment session including a data collection module in electronic communication with network servers for storage of data on non-transitory computer readable media for monitoring a patient's well-being during and after the treatment session. A method of using the system in treating a patient, by continuously, continually, or at the healthcare professionals discretion monitoring the well-being of the patient during a consciousness-altering therapeutic treatment session through one or more wearable devices and a patient mobile device in electronic communication with a facilitator mobile device, and continuously monitoring the well-being of the patient after the treatment session with the wearable device.

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.

Embodiments herein relate to ear-worn devices and, more specifically, ear-worn devices that can measure reaction and/or reflex speeds. An ear-worn device herein can include a control circuit, a clock circuit in electrical communication with the control circuit, a motion sensor in electrical communication with the control circuit, an electroacoustic transducer for generating sound in electrical communication with the control circuit, and a power supply circuit in electrical communication with the control circuit. The ear-worn device can be configured to initiate generation of a stimulus sufficient to generate a response from the ear-worn device wearer. The ear-worn device can be configured to monitor for a qualified response to the stimulus and measure an amount of time between the stimulus and the qualified response. Other embodiments are also included herein.

One of the objectives of this invention is to allow the conduction of audiometric evaluations in natural or artificial sound spaces, in a way that can be monitored and reproduced.

For that purpose, the inventors propose to create virtual environments which reproduce sound and visual characteristics of natural or artificial spaces.

In practice, a user experience is initiated between a subject and a virtual environment so as to simulate a specific audiometry test. Finally, a spatial auditory localization score is determined from measurements that will be carried out in the virtual environment.