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.

The process for classifying anesthetic depth includes: collecting of biological signals, conditioning of said signals, monitoring of activity of the central and autonomic systems, measurement of indexes and classification of patterns in anesthetic depth. The activity includes: i) Awake: Vigil—Ak. and recovery of verbal response—Rc. ii) Light Anesthesia: Light induction anesthesia—Li. Light recovery—Lr, Light dose, increase in drugs or patient movement (La), iii) General anesthesia: General anesthesia—Ga, one minute after the start of the surgery, and iv) Deep anesthesia: identification of the EEG burst-suppression pattern (BSP) associated with deep anesthesia.

Embodiments of the present systems and methods may provide a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease. For example, a method of detecting neurodegenerative disease may comprise measuring functioning of at least one of the motor system, cognitive function, and brain activity of a subject during everyday life and analyzing the gathered at least one motor system data, cognitive function data, and brain activity data of the subject.

A wearable medication adherence monitoring (MAM) device for wearing by a patient, including an operating unit (OU) which includes: a wireless communications unit (WCU); a processing unit (CPU); a memory unit; and one or a plurality of peripheral interface(s) with a plurality of input peripherals; and further includes the plurality of input peripherals and output peripherals in a MAM unit (MAMU) which includes: an interactive visual display unit (VDU) including a visual display (VD) and a VD patient interaction (PI) tool (VDTOOL); and an interactive audio platform (AP) including an audio output unit (SPK) and an audio PI tool (MIC; and one or a plurality of sensor unit(s) (SU(s)) including at least one biomarker sensor, and optionally at least one biometric sensor; included in one or a plurality of attachment units (AU) for wearing of the device on or about a body part of the patient.

A method of analyzing a patient's mental state, by automatically processing, integrating, and analyzing text-based and audio-based sources from the patient and clinical staff, and generating real-time outcomes and predictions. A system for processing, analyzing, and managing a patient's input including a data pool, model HUB, search service, topic modeling service, mental health related prediction service, and analytics all in electronic communication. A method of analyzing a patient, by processing, analyzing, and managing a patient's and clinical staff's text and audio input, and informing and augmenting diagnostic and prognostic processes, identifying improvement and deterioration of a patient's mental state, and identifying adverse events in psychotherapy, counseling, and other mental health management activities. A system for processing, analyzing, and managing clinical and diagnostic texts, and audio transcripts.

Examples of the present subject matter provide techniques for measuring stress levels using a variety of physiological indicators, such as pupil diameter, voice, cortisol levels, skin resistance, etc. Different sensors may be provided to measure the physiological indicators. Those measurements may be collected at a central server, where those measurements may be analyzed to determine the stress level of the user.

According to some aspects, disclosed methods and systems may include having a user input one or more speech commands into an input device of a user device. The user device may communicate with one or more components or devices at a local office or headend. The local office or the user device may transcribe the speech commands into language transcriptions. The local office or the user device may determine a mood for the user based on whether any of the speech commands may have been repeated. The local office or the user device may determine, based on the mood of the user, which content asset or content service to make available to the user device.

An apparatus and a method for caring emotion of a driver based on a vehicle sound, may include a detector configured to detect driving information of the vehicle and body information of a user, a non-transitory storage to store instructions, and a processor to execute the instructions. The processor determines an emotional status of the driver by use of at least one of the driving information or the body information, to generate a healing sound by designing a virtual sound based on the driving information and the emotional status of the driver, and to generate and output the healing sound.

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.

An audio system for user hearing assessment includes one or more audio capture devices, and processing circuitry. The one or more audio capture devices are configured to capture audio of a conversation of a user and convert the audio to audio signals. The processing circuitry is configured to use the audio signals to identify multiple conditions associated with user hearing difficulty. The conditions include any of words, phrases, frequencies, or phonemes, and environmental audio conditions that are followed by an indication of user hearing difficulty. The processing circuitry is configured to generate a hearing profile for the user based on the identified conditions associated with user hearing difficulty. The processing circuitry is configured to adjust an operation of an audio output device using the hearing profile to reduce a frequency of user hearing difficulty if the user requires audio enhancement.