142 results about "Event-related potential" patented technology

A neuro-informatics repository system is provided to allow efficient generation, management, and access to central nervous system, autonomic nervous system, effector data, and behavioral data obtained from subjects exposed to stimulus material. Data collected using multiple modalities such as Electroencephalography (EEG), Electrooculography (EOG), Galvanic Skin Response (GSR), Event Related Potential (ERP), surveys, etc., is stored using a variety of data models to allow efficient querying, report generation, analysis and/or visualization.

A system determines neuro-response stimulus and stimulus attribute resonance. Stimulus material and stimulus material attributes such as communication, concept, experience, message, images, audio, pricing, and packaging are evaluated using neuro-response data collected with mechanisms such as Event Related Potential (ERP), Electroencephalography (EEG), Galvanic Skin Response (GSR), Electrocardiograms (EKG), Electrooculography (EOG), eye tracking, and facial emotion encoding. Neuro-response data is analyzed to determine stimulus and stimulus attribute resonance.

The ACSSECR invention is a biometric access control system and methodology that measures cognitive, psychophysiological responses to stimuli to confirm the identity of an individual. As an alternative to “Logging in” with a user ID and password, this cognitive biometric authentication system is used for “Cogging in” to a system with user ID and user-selected “Cogkey”. ACSSECR is designed for strict access control scenarios where significant authentication confidence is required to gain access to controlled information, facilities, systems, vehicles, or devices. The system takes advantage of a behavioral and physiological characteristic of humans that is an unconscious response to a stimulus. The Event Related Potential (ERP) response (specifically the P3 ERP) involuntarily occurs when an individual perceives and reacts to an unexpected, task-relevant event. The task is for the user to recognize their Cogkey which is presented infrequently amidst more frequent non-target stimuli. There is no requirement for extensive enrollment by users, only the recognition of their Cogkey. The basic system does not store biometric data for comparison, but rather measures the user's Cogkey recognition responses in comparison to non-Cogkey stimulus responses. An individual can have multiple personas with different Cog keys.

A system for developing a brain-computer interface (BCI), especially for use in rehabilitation, includes an audio-visual interface device for applying to a subject being examined stimuli eliciting event-related potentials and inducing brain reactions in said subject being examined. The system further includes an acquisition device for acquiring brain reaction signals (such as EEG traces) of the subject being examined synchronized with the stimuli and at least one processing device for processing the signals acquired via said acquisition device, The interface device, the acquisition device and the processing device comprise an integrated system. Preferably, the system uses a p300 signal as the event-related potential.

The control method for a device includes steps of: presenting a visual stimulation concerning a manipulation menu for a device; measuring event-related potentials after the visual stimulation is presented, where event-related potentials based on a timing of presenting the visual stimulation as a starting point are measured from a potential difference between each of electrodes and at least one reference electrode respectively worn on a face and in an ear periphery of a user; from each of the measured event-related potentials, extracting electroencephalogram data which is at 5 Hz or less and contains a predetermined time section, and combining the extracted electroencephalogram data into electroencephalogram characteristic data; comparing the electroencephalogram characteristic data against reference data prepared in advance for determining a desire to select an item in the manipulation menu; and, based on a comparison result, executing a manipulation of the device corresponding to the item.

An eyeglass-type electroencephalogram interface system is worn on the head of a user. The system includes: an output section for presenting a visual stimulation to the user; an ear electrode portion disposed at a position coming in contact with an ear of the user when the system is worn; a facial electrode portion disposed at a position coming in contact with the face below a straight line connecting an external canthus and an internal canthus of an eye of the user, such that the mass of the system is supported at the position, when the system is worn; and an electroencephalogram measurement and determination section for measuring an event-related potential on the basis of a potential difference between the ear electrode portion and the facial electrode portion based on the visual stimulation being presented by the output section as a starting point.

In a system having an interface utilizing electroencephalograms, a user's burden of calibration for accurately measuring electroencephalograms is eliminated, and it becomes possible to maintain a high distinction accuracy of electroencephalograms.

An electroencephalogram interface (IF) system 1 includes an electroencephalogram IF section (13) for distinguishing a request of a user based on electroencephalograms, and identifies a function which is in accordance with the request. An electroencephalogram distinction method adjustment apparatus (2, 50) includes: an analysis section (14, 52) for detecting a change in a characteristic quantity of a stimulation given to the user, thus detecting a change in the stimulation; a storage section (15) for storing a waveform of an event-related potential during a period after a point in time when the change in the stimulation is detected; an extraction section (16) for extracting a characteristic quantity of the user based on the stored waveform; and an adjustment section (17) for, based on the extracted characteristic quantity, adjusting in the electroencephalogram IF section (13) a distinction method for a request based on an electroencephalogram signal.

A method for analysis of the extent of conscious awareness and likelihood of recovery of a patient includes the steps of applying to the patient a sensory stimulus sequence which is typically auditory; carrying out an EEG to generate waveform signals to record changes in the electromagnetic fields generated by the patient's neural activity; using software provided in a processor to process the waveform signals in order to locate waveform peaks, identify the event-related potential (ERP) components obtained in the waveform and to obtain quantitative measures of those components; and using the software to generate and communicate scores indicative of the extent of conscious awareness and likelihood of recovery of the patient.

An electroencephalogram interface is activated by utilizing a biological signal, in particular a steady-state visual evoked potential, from a user.

An electroencephalogram interface system (1) includes a biological signal detection section (4) for detecting an electroencephalogram signal from a user (3) and a control section (5) for distinguishing a component of an event-related potential which is contained in the electroencephalogram signal and causing a device to operate based on the distinguished event-related potential. The electroencephalogram interface system (1) further includes an activation apparatus (2) for activating the control section (5) and an output section (6) for presenting a visual stimulation which flickers with a predetermined frequency based on a signal from the activation apparatus (2). The activation apparatus (2) includes: a frequency analysis section (7) for analyzing a frequency component of the electroencephalogram signal detected by the biological signal detection section (4), and detecting an intensity corresponding to the predetermined frequency; and a determination section (8) for comparing the detected intensity of the predetermined frequency and a predetermined threshold, and if the intensity of the predetermined frequency is equal to or greater than a predetermined threshold, determining that the user (3) has been paying attention to the visual stimulation and thus activating the control section (5).

A driving attention amount determination apparatus includes: an electroencephalogram measurement section for measuring an electroencephalogram signal of a driver; a central stimulation presentation section for presenting a visual stimulation in a central visual field of the driver; a peripheral stimulation presentation section for presenting a visual stimulation in a peripheral visual field of the driver; a threshold setting section for setting a determination threshold for attention amount determination from a distribution of amplitude of an event-related potential in the electroencephalogram signal based on a point of presenting the stimulation in the central visual field as a starting point; and an attention amount determination section for determining an attention amount through a comparison between the determination threshold and an amplitude of an event-related potential in the electroencephalogram signal based on a point of presenting the stimulation in the peripheral visual field as a starting point.

A collimator, and in particular a method for making a collimator for use with a small high resolution single-photon emission computed tomographic (SPECT) imaging tool for small animal research. The collimator is sized, both functionally and structurally, particularly smaller than known collimators and appropriately scaled to achieve a highly sensitive collimator which facilitates desired reconstruction resolutions for small animals, as well as compliments other functional imaging modalities such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and event-related potential (ERP), magneto-encephalography (MEG), and near-infrared optical imaging.

An universal test system based on microcomputer for testing the nervous behaviour is composed of the irritation reaction multimedia subsystem and the cerebral current/cognitive level recording-analyzing subsystem, both of which are connected via serial communication parts. The former can make the video-audio irritation its ns precision, record the reaction of the person to be tested, and send outrelative event. The latter is composed of 5 functional modules (data acquisition, cerebroelectric wave classification, average superimpose, total average and multi-domain analysis) and digitalized cerebroelectric amplifier.

The invention discloses a method for optimizing an audio-visual cognitive event-related potential experimental paradigm. The method comprises the following steps of: on the basis of two first optimal Oddball sequences, performing combined stimulation of different matching modes of target stimulation and background stimulation modes on each subject respectively to induce a cognitive electroencephalographic experiment, establishing a plurality of second Oddball sequences, synchronously recording a plurality of second electroencephalographic signals, performing off-line analysis, and acquiring a plurality of second event-related potential data; acquiring the second Oddball sequence which corresponds to the second event-related potential data with the highest identification correct rate, wherein the second Oddball sequence is taken as a second optimal Oddball sequence of each subject; and gradually changing the appearance proportion of target stimulation, the duration and the stimulation interval of each subject in the second optimal Oddball sequence to induce cognitive electroencephalographic signals, acquiring a plurality of event-related potential data respectively, performing off-line analysis, and constructing an effective Oddball sequence scheme. The method is used for the auxiliary identification of the target stimulation, and can accurately position the target stimulation.

A mental work load detector arranged to sense the electroencephalogram of a person and estimate a mental work load on the perceptual-motor system and a mental work load on the perceptual-central processing system separately from each other includes a electroencephalogram sensor arranged to sense the electroencephalogram of a rider, an eye fixation-related potential detector arranged to detect an eye fixation-related potential by analyzing the electroencephalogram and to detect a lambda response, an event-related potential measuring device arranged to measure an event-related potential in response to a sound from a speaker and to detect auditory p300, a lambda response comparator arranged to determine whether the lambda response has decreased, an auditory p300 comparator arranged to determine whether the auditory p300 has decreased, and a mental work load determiner arranged to determine that the mental work load on the perceptual-central processing system has increased if the lambda reaction and the auditory p300 has decreased and that the mental work load on the perceptual-central processing system has increased if the auditory p300 has decreased but the lambda response has not decreased.

The invention relates to a classification and recognition method for P300 event-related potential based on deep learning, and belongs to the technical field of medical and physiological signal detection and processing analysis. According to the invention, a Butterworth filter is adopted to successively perform high-pass filtering and low-pass filtering on original signals to remove artifacts and power frequency interference; the data is amplified by using a one-time superposition averaging technique, normalization and time domain truncation are performed on EEG signals, and corresponding supervisory signals are formulated according to the signal types; the EEG data is divided into a training set and a verification set after data preprocessing, a deep learning network capable of classifyingand recognizing the P300 event-related potential is constructed, and the feature extraction ability of the network is improved; the probability that an input signal contains the P300 event-related potential is finally predicted through the trained network; and finally, a target character is predicted according to an experimental paradigm and the probability value outputted by the network. The experiment shows that the algorithm is good in performance and can also obtain good character recognition accuracy under the condition of reducing the number of experiments.

There is provided a technique which, in the case where the operation has not occurred in a manner as expected by the user, determines from which standpoint the operation was not as expected, and makes a response that is closer to the expectation.

An information processing system according to the present invention includes: a reaction section for executing a first process based on a request from a user; an output section for outputting a result of a process; a signal detection section for measuring a signal concerning an event-related potential of electroencephalograms of the user; an analysis section for identifying a positive peak in the event-related potential and determining whether an elapsed time since the result is output and until the peak appears is closer to a first reference time or a second reference time; and a reaction modifying section for determining a second process in accordance with the determination result. This determination result indicates a degree of disappointment of the user, and the second process is to be determined in accordance with the degree. By the reaction section executing the second process, an operation is realized which conforms to the user's expectation even if the operation has not occurred in a manner as expected by the user.