An electrode system for an intracranial electroencephalogram is described. A substrate is configured to be applied directly on a brain of a patient. The substrate has a profile that is suitable to be placed within a subdural space in between a portion of intact cranium and cerebral cortex of the brain. A tracking device is arranged on the substrate. A plurality of electrodes are configured to sense electrical activity associated with the brain. Each of the plurality of electrodes has a predefined relationship with the tracking device. A tracking system is operable to determine a position of the tracking device relative to a reference point based on a strength of an electromagnetic field relative to the tracking device. A controller is configured to selectively determine a position for each of the plurality of electrodes based on the position of the tracking device and the predefined relationship.

An intelligent psychological assessment and intervention system based on an independent space, comprising a psychological intervention cabin and a central database which achieves data interaction with the psychological intervention cabin. The psychological intervention cabin comprises a housing, a data acquisition module, a data processing module, and an intervention module; the data acquisition module acquires physiological and psychological data of a subject; the data processing module performs operations on the acquired data, establishes a multi-dimensional state point of the subject according to a mathematical model of the data processing module, matches it with data in the central database, finds a suitable intervention procedure for the subject, and guides the intervention module to carry out intervention; in the intervention process, the data acquisition module continuously acquires the physiological and psychological data of the subject, and the data processing module forms a new multi-dimensional state point according to new data and re-matches it to adjust the intervention procedure. By repeating this cycle, the intervention procedure is continuously adjusted in the intervention process to seek a most suitable intervention solution for the subject, and an optimal intervention effect is achieved.

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 present invention is a human centric lighting (HCL) method with adjustable lighting parameters comprises the following steps: 1) User connects with the cloud through the intelligent communication device and selects the specific spectral recipe that the user wants to achieve a specific emotion from the cloud; 2) The light emitting device is configured to emit light in a specific light field according to the lighting parameters in a specific light field to select the light in a specific light field; 3) After the user performs HCL, when the effect of specific emotion is not reached, the user adjusts the lighting parameters in the selected specific spectral recipe through the intelligent communication device; 4) When the user has achieved the effect of specific emotion after performing HCL, store the corresponding lighting parameters of the adjusted spectral recipe to the cloud.

Provided are a method, apparatus, and computer program for creating a standardized brainwave image for training an artificial intelligence model. The method of creating a standardized brainwave image for training an artificial intelligence model executed by a computing device according to various embodiments of the present invention includes collecting a plurality of brainwave signals of a user, processing the plurality of collected brainwave signals, and creating a brainwave image using the plurality of processed brainwave signals.

Proposed is system and method for determining a driver's fatigue to promote safe driving by determining the driver's fatigue according to a change in a brain wave of a driver during driving of a vehicle.

Proposed is system and method for determining a driver's fatigue to promote safe driving by determining the driver's fatigue according to a change in a brain wave of a driver during driving of a vehicle.

Systems and method for monitoring patient physiological data are presented herein. In one embodiment, a physiological sensor and a mobile computing device can be connected via a cable or cables, and a processing board can be connected between the sensor and the mobile computing device to conduct advanced signal processing on the data received from the sensor before the data is transmitted for display on the mobile computing device.

Systems and method for monitoring patient physiological data are presented herein. In one embodiment, a physiological sensor and a mobile computing device can be connected via a cable or cables, and a processing board can be connected between the sensor and the mobile computing device to conduct advanced signal processing on the data received from the sensor before the data is transmitted for display on the mobile computing device.

A system (1) for estimating the brain blood volume and/or brain blood flow and/or depth of anesthesia of a patient, comprises at least one excitation electrode (110E) to be placed on the head (20) of a patient (2) for applying an excitation signal, at least one sensing electrode (110S) to be placed on the head (20) of the patient (2) for sensing a measurement signal caused by the excitation signal, and a processor device (12) for processing said measurement signal (VC) sensed by the at least one sensing electrode (110S) for determining an output indicative of the brain blood volume and/or the brain blood flow. Herein, the processor device (12) is constituted to reduce noise in the measurement signal (VC) by applying a non-linear noise-reduction algorithm. In this way a system for estimating the brain blood volume and/or the brain blood flow of a patient is provided which may lead to an increased accuracy and hence more exact estimates.