96 results about "Cognitive status" patented technology

Portable transdermal electrical stimulation (TES) applicators for modifying a subject's cognitive state. In general, the portable applicators described are specifically configured and adapted to be lightweight and may be wearable, and to deliver a high-intensity TES able to evoke or enhance a predetermined cognitive effect. These TES applicators may include a pair of electrodes and a TES control module comprising a processor, a timer and a waveform generator. TES control module is adapted to deliver a biphasic electrical stimulation signal of 10 seconds or longer between the first and second electrodes having a frequency of 400 Hz or greater, a duty cycle of greater than 10 percent, an intensity of 3 mA or greater, with a DC offset.

A method of and apparatus for monitoring and intervening in, in real time, a collaboration between a plurality of subjects comprising measuring indicia of physiological and cognitive states of each of the plurality of subjects, communicating the indicia to a monitoring computer system, with the monitoring computer system, comparing the indicia with one or more models of previous collaborative performance of one or more of the plurality of subjects, and with the monitoring computer system, employing the results of the comparison to communicate commands or suggestions to one or more of the plurality of subjects.

Disclosed embodiments provide cognitive state evaluation for vehicle navigation. The cognitive state evaluation is accomplished using a computer, where the computer can perform learning using a neural network such as a deep neural network (DNN) or a convolutional neural network (CNN). Images including facial data are obtained of a first occupant of a first vehicle. The images are analyzed to determine cognitive state data. Layers and weights are learned for the deep neural network. Images of a second occupant of a second vehicle are collected and analyzed to determine additional cognitive state data. The additional cognitive state data is analyzed, and the second vehicle is manipulated. A second imaging device is used to collect images of a person outside the second vehicle to determine cognitive state data. The second vehicle can be manipulated based on the cognitive state data of the person outside the vehicle.

A system and method for improving student learning includes learning material that is presented to a student and a device that is used to acquire physiological data from the student in real time during a learning session. A cognitive assessment algorithm determines a cognitive state of the student using the physiological data, and a learning action algorithm modifies the presentation of the learning material in response to the student's cognitive state. The learning material can include lectures, questions asked of the student or problems or activities being completed by the student. In one embodiment, the device directly measures the brain activity of the student to determine the student's cognitive state. The cognitive state of the student can include the student's cognitive load, engagement or fatigue.

Methods for allowing a user to control a neuromodulator to modify a cognitive state being experienced by the user. The user may select a waveform ensemble from a hand-held user device having an interface, and the user may adjust the perceived intensity of the applied waveform ensemble with the user device while the waveform ensemble is being applied. Also described are methods of managing communication between the hand-held user device (such as a smartphone or the like) and a wearable neurostimulator. Methods of displaying and visually tracking and controlling the applied waveform ensemble are also described herein.

Methods and apparatuses for controlling a wearable neurostimulator from a control apparatus. Described herein are methods and apparatuses for controlling the application of ensemble waveforms using a transdermal electrical stimulation by a neurostimulator having a processor. The controller may provide specifically configured commands to efficiently and accurately control the delivery of an ensemble waveform by the neurostimulator, wherein the ensemble waveform includes a sequence of component biphasic current waveforms in which one or more parameters (such as frequency, current amplitude, percent duty cycle, and percent charge imbalance) vary between sequential component waveforms particularly effective at evoking a desired cognitive state by TES.

A breathing assistance unit for providing pressurized heated humidified air at to a user is configured to increase user compliance. The breathing assistance unit comprises means for generating positive emotional and cognitive states of a user about the therapy.

The invention discloses a cerebrum cognitive status recognition method based on cerebral function imaging, comprising the following steps of: inputting experimental data series of cerebral nuclear magnetic resonance images; preprocessing the experiment data of the cerebral nuclear magnetic resonance images; establishing a multidimensional data set which includes a cerebrum coordinate dimension, acerebrum area dimension, an experiment time sequence dimension and a cognitive status dimension; extracting features; classifying and identifying the statuses. The invention extracts feature vectors from cerebral images of cerebra knowing the task statuses to train a support vector classifier, and classify the cognitive status for the feature vectors of an unknown cerebral image using the classifier. If the unknown cerebral image belongs to some category, then the cognitive state the category belongs to is identified as the cognitive status of the unknown cerebral image, thereby achieving theaim of cerebrum cognitive status recognition. The multidimensional data set of cerebral images of the invention are used for secondary analysis, treatment and integration of the cerebral images, thereby enabling the data calculation and analysis of the cerebral images to be more convenient, faster and more visual.

An apparatus and method of collecting elements of and assembling various portions of ocular micro motions such as ocular micro-tremor (OMT) movements of the eye, and correlating them directly with OMT waveforms acquired from both known and unknown states of cognition and cognitive function. Comparing newly acquired waveforms from patients with undiagnosed cognitive dysfunctions, permits an individual or caregiver the ability to identify those unknown issues or cognitive states based on matching or relating statistically elements of their waveform with categories of other known cognitive processing normals and abnormals, functional and dysfunctional individuals. It also allows for measuring the effects of therapeutic agents (psychological or pharmacological) by relating them to measurable changes in cognitive function as a result of correlated changes in waveforms.

Disclosed is a brain cognitive state judgment method based on a non-negative tensor projection operator decomposition algorithm. The method includes the steps of S1, collecting brain functional magnetic resonance images under different cognitive tasks to form a data sample set, carrying out preprocessing, and forming a sample set according to tensor modes, wherein the sample set is divided into a training set and a testing set according to the cognitive tasks, and the training set comprises functional magnetic resonance data in similar proportion of different cognitive states, S2, computing non-negative tensor projection operator decomposition of the training sample set to solve out a non-negative feature transformation matrix, projecting training samples to a non-negative tensor feature sub-space for dimensionality reduction to obtain a non-negative feature tensor set of the training set, S3, using lower-dimension non-negative feature tensor data after dimensionality reduction as input of an STM for training to solve out the optimum projection direction of the STM, and S4, projecting brain functional magnetic resonance data of tested samples to the non-negative tensor feature sub-space obtained through training to obtain non-negative feature tensors of the brain functional magnetic resonance data in the sub-space, and inputting the non-negative feature tensors of the tested samples to the trained STM to judge cognitive state types of the non-negative feature tensors.

Aspects of the present disclosure are directed to devices, systems, and methods for optimized integration of a human operator with a machine for safe and efficient operation. Accordingly, aspects of the present disclosure are directed to systems, methods, and devices which evaluate and determine a cognitive state of an operator, and allocate tasks to either the machine and / or operator based on the cognitive state of the operator, among other factors.

A file system storing an executive program and a plurality of modules such that when the executive program is executed by a processor the executive program controls the plurality of modules. The modules include a plurality of test modules for executing a specific individual test to test a cognitive attribute of a user; a plurality of test batteries having one or more specified test modules, at least one registration module for registering each of the plurality of users; a plurality of interpretive modules for interpreting results of the test batteries; and at least one report module for immediately generating a cognitive status report for reporting the test battery results as determined by the plurality of interpretive modules.

The embodiment of the invention provides a personality assessment method and system based on neural response. The personality assessment method comprises the steps that personality test materials in apreset material library are played to a tester, and the electroencephalogram signals of the tester are received; the response characteristic in the electroencephalogram signals is extracted to establish a response characteristic vector; and the response characteristic vector is input into a preset personality characteristic regression model, and the personality characteristic index of the testeris calculated through the personality characteristic regression model. The response characteristic is the average value of personality related electroencephalogram components of the tester within a preset time range after the tester watches the preset personality test materials. According to the personality assessment method, the personality characteristic related cognitive state of the tester isinduced through specific materials, and the electroencephalogram signals in the process are recorded, so that the personality characteristics of the tester are judged according to the electroencephalogram signals, and the personality characteristics can be assessed more accurately and truly based on objective electroencephalogram data.