An improved system for assessing cognitive function is described that uses tracked electrical activity of the brain of the individuals in response to a specific sequence of stimuli in generating data sets, which, for example, can be encapsulated as a data structure. The data sets can include tracked specific response types, at different times and amplitudes, including, but not limited to, event related potential signal components. Brainwave features including, event related potentials, are tracked in relation to both pre-attentive brain responses and consciously controlled attention responses.

The present invention relates to a wearable sensor device and method for a thermogenic and/or psychogenic stress response of a subject. The wearable sensor device comprises a first electrode (11) configured to contact a first non-glabrous skin part of the subject, a second electrode (12) configured to contact a second non-glabrous skin part of the subject, a third electrode (13) configured to contact a glabrous skin part of the subject, and a skin conductance sensor (14) configured to provide a voltage signal between a positive input terminal (141) and a negative input terminal (142) and to measure a skin conductance signal at an output terminal (143). A switching arrangement (15) switches connections between the first to third electrodes and the positive and negative input terminals of the skin conductance sensor between at least three switching states. A processing unit (15) determines a 10 thermogenic and/or sychogenic stress response from the measured skin conductance signals during the at least three switching states.

The present invention relates to a wearable sensor device and method for a thermogenic and/or psychogenic stress response of a subject. The wearable sensor device comprises a first electrode (11) configured to contact a first non-glabrous skin part of the subject, a second electrode (12) configured to contact a second non-glabrous skin part of the subject, a third electrode (13) configured to contact a glabrous skin part of the subject, and a skin conductance sensor (14) configured to provide a voltage signal between a positive input terminal (141) and a negative input terminal (142) and to measure a skin conductance signal at an output terminal (143). A switching arrangement (15) switches connections between the first to third electrodes and the positive and negative input terminals of the skin conductance sensor between at least three switching states. A processing unit (15) determines a 10 thermogenic and/or sychogenic stress response from the measured skin conductance signals during the at least three switching states.

The present disclosure is directed to systems and methods for measuring and analyzing pupillary psychosensory responses. An electronic device is configured to receive video data with at least two frames. The electronic device then locates one or more eye objects in the video data and determine pupil and iris sizes of the one or more eye objects. The electronic device determines the pupillary psychosensory responses of the one or more eye objects by tracking a ratio of pupil diameter to iris diameter throughout the video. Several metrics for the pupillary psychosensory responses can be determined (e.g., velocity of change of the ratio, peak to peak amplitude of the change in ratio over time, etc.). These metrics can be used as measures of an individual's cognitive ability and mental health in a single session or tracked throughout multiple sessions.

A condition visualization system includes a first acquisition unit, an estimation unit, a processing unit, an output unit, a second acquisition unit, and a correction information generation unit. The first acquisition unit acquires a user's biometric information. The estimation unit obtains, based on the biometric information, an estimated value representing the user's mental and physical condition. The processing unit generates, based on the estimated value, mental and physical condition information. The output unit outputs the mental and physical condition information to a display unit. The second acquisition unit acquires a subjective value with respect to the user's mental and physical condition. The correction information generation unit generates correction information by using a plurality of data sets, each including the estimated value and the subjective value. The processing unit generates the mental and physical condition information by making correction to the estimated value based on the correction information.

A condition visualization system includes a first acquisition unit, an estimation unit, a processing unit, an output unit, a second acquisition unit, and a correction information generation unit. The first acquisition unit acquires a user's biometric information. The estimation unit obtains, based on the biometric information, an estimated value representing the user's mental and physical condition. The processing unit generates, based on the estimated value, mental and physical condition information. The output unit outputs the mental and physical condition information to a display unit. The second acquisition unit acquires a subjective value with respect to the user's mental and physical condition. The correction information generation unit generates correction information by using a plurality of data sets, each including the estimated value and the subjective value. The processing unit generates the mental and physical condition information by making correction to the estimated value based on the correction information.

A state of a cognitive function can be determined by using biological information measured as part of daily healthcare management. A biological information acquisition device includes a cognitive function test unit for testing a cognitive function, a biological information acquisition unit for performing biological information acquisition processing for acquiring biological information of a user, and a cognitive function determination unit for determining a state of the cognitive function, wherein the cognitive function determination unit determines the state of the cognitive function based on a result of the cognitive function test and the biological information acquired from the user.

The present invention relates to a cognitive function test server, including a communication interface, a memory; and a processor which is operably connected to the communication interface and the memory, and the processor is configured to provide a first sequence to acquire brainwave data of a user in a resting state by means of an HMD device, acquire baseline brainwave data of the user based on the first sequence, provide at least one second sequence related to a cognitive function by means of the HMD device, acquire input data and activated brainwave data based on the second sequence from the HMD device and an input device connected thereto, and generate a cognitive evaluation result of the user based on at least one of the reference brainwave data, the activated brainwave data, and the input data of the user.

A system includes an electronic contact lens that obtains sensor measurements from integrated motion sensors or other types of sensors and a processing module that estimates a mental state of an individual based on the sensor measurements. The processing module identifies patterns of eye movements and analyzes how these patterns change over time. Based on anatomical relationships between eye movement and mental state, the processing module estimates characteristics of the individual such as fatigue, intoxication, injury, or a medical condition that have known effects on eye movement patterns. The electronic contact lens system generates an output indicative of the estimated mental state to alert the individual to the detected condition or to initiate an automated action.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.