447 results about "Brain computer interfacing" patented technology

An electrocorticography-based brain computer interface (BCI) and related methods are described.

The present invention discloses an architecture of an embedded internet robot system controlled by brain waves, wherein the brain-computer interface and the internet robot system cooperate with the alertness level detection technology and the instruction translation technology, and thereby, the user can control a distal-end robot purely via consciousness activities and can interact with the environment as if there were an entity representing the user's consciousness appearing in the distal end. The seriously disabled person can regain his expressive ability via the present invention. Further, the present invention can also be applied to a multi-player interactive game system.

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.

A noninvasive brain computer interface (BCI) system includes an electroencephalography (EEG) electrode array configured to acquire EEG signals generated by a subject. The subject observes movement of a stimulus. A computer is coupled to the EEG electrode array and configured to collected and process the acquired EEG signals. A decoding algorithm is used that analyzes low-frequency (delta band) brain waves in the time domain to continuously decode neural activity associated with the observed movement.

The invention provides a system and method for controlling a brain computer interface (BCI) based on multimode fusion. The system comprises a brain electrostimulation and feedback module, an electroencephalogram (EEG) signal acquisition module, an EEG signal processing module and an execution module, wherein the brain electrostimulation and feedback module is used for evoking an SSVEP (Steady State Visual Evoked Potential) and inducing an MI (Motor Imagery); the EEG signal acquisition module is used for acquiring EEG signals; the EEG signal processing module is used for extracting, identifying and classifying SSVEP characteristics and MI EEG characteristics in the EEG signals and feeding classified results which respectively correspond to the SSVEP characteristics and the MI EEG characteristics back to the brain electrostimulation and feedback module; and the execution module is used for executing the classified results. According to the system and the method, a multimode fusion BCI is constructed, so that the information transmission rate, reliability and flexibility of a control system are improved, the low information transmission rate of a BCI in a single MI mode is reduced, meanwhile, the visual burden under a single SSVEP task is reduced, and the adaptation crowds of the BIC-based control system are increased.

A method and system provides for headgear usable for electrophysiological data collection and analysis and neurostimulation / neuromodulation or brain computer interface for clinical, peak performance, or neurogaming and neuromodulation applications. The headgear utilizes dry sensor technology as well as connection points for adjustable placement of the bi-directional sensors for the recoding of electrophysiology from the user and delivery of current to the sensors intended to improve or alter electrophysiology parameters. The headgear allows for recording electrophysiological data and biofeedback directly to the patient via the sensors, as well as provide low intensity current or electromagnetic field to the user. The headgear can further include auditory, visual components for immersive neurogaming. The headgear may further communication with local or network processing devices based on neurofeedback and biofeedback and immersive environment experience with balance and movement sensor data input.

The invention discloses a brain-computer interface system based on an atom magnetometer, and a use method thereof. The invention combines the work characteristics of the atom magnetometer to design abrain magnetic cap and a magnetic shielding device with practicality; a scheme of separating an atom magnetometer probe from a light source is adopted to improve a system integration level; system probability is intensified; a brain magnetic signal processing process capable of greatly improving operation speed and reducing processing process complexity; and for scenes which may be applied by thesystem, a feasible commutation and peripheral support system is given. By use of the brain-computer interface system provided by the invention, the control of a local and remote application system isfinished conveniently through the brain magnetic signal, and the system owns practicality and good expansion performance.

A method and system provides for headgear usable for electrophysiological data collection and analysis and neurostimulation / neuromodulation or brain computer interface for clinical, peak performance, or neurogaming and neuromodulation applications. The headgear utilizes dry sensor technology as well as connection points for adjustable placement of the bi-directional sensors for the recoding of electrophysiology from the user and delivery of current to the sensors intended to improve or alter electrophysiology parameters. The headgear allows for recording electrophysiological data and biofeedback directly to the patient via the sensors, as well as provide low intensity current or electromagnetic field to the user. The headgear can further include auditory, visual components for immersive neurogaming. The headgear may further communication with local or network processing devices based on neurofeedback and biofeedback and immersive environment experience with balance and movement sensor data input.

Electrical activity of the brain (EEG) and position / motion of a body part, e.g. motion of an arm, are measured. A virtual representation of either the moving body part or the intended movement as determined from the brain activity is presented as feedback to the subject on a display which can be implemented as a head-up display. A clock module is operable to time stamp information transferred from a brain electrical activity sensing system and a position / motion detection system for joint processing. This non-invasive EEG-based brain-computer-interface is particularly useful for stroke rehabilitation.

A method of classifying an image is disclosed. The method comprises: applying a computer vision procedure to the image to detect therein candidate image regions suspected as being occupied by a target; presenting to an observer each candidate image region as a visual stimulus, while collecting neurophysiological signals from a brain of the observer; processing the neurophysiological signals to identify a neurophysiological event indicative of a detection of the target by the observer; and determining an existence of the target in the image is based, at least in part, on the identification of the neurophysiological event.

A brain-computer interface device and method for controlling the motion of an object is provided. The brain-computer interface device includes a brain wave information processing unit, which receives converted brain wave information including object motion information, extracts object control information including the object motion information from the converted brain wave information, and transmits the extracted object control information to a hybrid control unit, and a hybrid control unit which receives target information including target location information of a target and outputs final object control information obtained by correcting the object control information including the object motion information based on the target information.

The invention relates to a robot system based on a brain-computer interface and an implementation method. The robot system is mainly characterized in that a brain-computer interface sub-system obtains a brain electrical signal through a measurement electrode and performs feature extraction of the brain electrical signal to obtain the intention of a user; the brain-computer interface sub-system converts the intention of the user into a control command and transmits the control command to a robot sub-system through a communication sub-system; the robot sub-system receives the control command of the brain-computer interface sub-system and controls a robot to move; the robot sub-system transmits video information acquired by self to the brain-computer interface sub-system; and the brain-computer interface sub-system forms a stimulation interface fed back to the user. According to the invention, mobility control of the robot in eight directions through the steady-state visual evoked potential brain-computer interface can be realized; furthermore, the system can control the robot rapidly and precisely without being trained; because the brain-computer interface is free from body movement participation, the user suffering from severe dyskinesia can move to an expected position; and thus, the living quality is increased.

The invention discloses an intelligent wheel chair control method based on a brain-computer interface and an automatic driving technology. The method comprises the following steps: obtaining current pictures by a network camera to position a barrier; generating a candidate destination by the information of the barrier, and a track point for planning a path; automatically positioning a wheel chair; selecting the destination by a user through the brain-computer interface; planning the optimal path by combining the track point and by using the current position of the wheel chair as the starting point and the destination selected by the user as the end point; calculating the position difference between the current position of the wheel chair and the optimal path to be used as the feedback of a PID path tracking algorithm; calculating the reference angular speed and the reference linear speed according to the PID path tracking algorithm to be incorporated into a PID movement controller, converting mileage data into current angular speed and linear speed information to be used as the feedback of the PID movement controller, and controlling the wheel chair in a real-time way to drive to the destination. For the method, the mental burden of a user is greatly relieved, the method can adapt to various environments, and the self-care ability of a paralytic patient with serious illness is improved.

The invention relates to an extraction method of EEG characteristics of imagination of single-side limb motion in a brain-computer interface device. The classification of the characteristics of imagination of single-side motion has stronger pertinence, which is decided by the nature of excluding same tasks and extracting different tasks of a CSP space filtering method; at the same time, due to the combination of CSP algorithm and FDA characteristics extraction, the dimension of input vectors is reduced, and the marketability of a classifier is enhanced; therefore, the classification accuracy rate is enhanced to a certain extent; adopting Fisher Differentiation and Analysis (FDA), ten-dimension input vector v1, v2(v1 is four-dimension, and v2 is six-dimension) are reduced into two one-dimension input vectors f1, f2, and then classification is carried out by a support vector machine, thereby not only improving classification accuracy rate, but also avoiding the problem of dimension disaster caused by too high dimension ,as well as being beneficial to the popularization of the classifier.

The invention discloses an extraction method for brain-computer interface system imagination action EEG signal features, in particular to an EEG feature extraction method based on a wavelet transform and a BP neural network. The invention takes the energy change caused by imagination action thinking to be a feature distinguishing the imagination movements of a left hand and a right hand, respectively calculates the point-to-point average power of the entire samplings of the EEG signal obtained from C3 and C4 channels by the left hand and the right hand through the imagination (thereinafter called as C3 and C4 of the left hand and the right hand) within 0 to 9s according to the average power formula. A time window is arranged, a discrete dyadic wavelet transform is made to the data of a section provided with the window, an approximation signal a6 on a sixth size is selected to be taken as a signal feature; a BP neural network is used as a classifier to classify. The method of the invention adopting the wavelet transform and the BP neural network to extract the potential of the imagination movement helps to improve the signal / noise ratio and the identification correction rate of the potential of the imagination action; in addition, the wavelet transform is a linear transform, has a quick calculation speed, and is suitable for on-line analysis.

A closed-loop brain computer interface (BCI) system for treating mental or emotional disorders with responsive brain stimulation is disclosed. The system includes an implanted module including a processor configured to process neural data acquired from one or more electrodes in communication with one or more brain regions of a patient. The implanted module is configured to deliver stimulation to electrodes in contact with the brain regions. An interface is in wireless communication with the implanted module and configured to receive the neural data from the implanted module. A controller processes the patient's brain and body signals to provide patient intentional control over the stimulation applied to the one or more electrodes and to control the stimulation.

Provided is a mixing method for a brain-computer interface based on SSVEP and OSP. A subject wears an electrode cap. A SSVEP-OSP mixed paradigm is broadcast in front of the subject by means of a computer screen. The subject stares at any one of simulation units. By a collection system, an electroencephalogram signal generated when the subjects stares at a simulation target is magnified, filtered and subjected to analog-digital conversion by an electroencephalogram acquisition instrument. Digitized electroencephalogram data is inputted into a computer. An electroencephalogram signal feature extraction method based on a typical correlation analysis is adopted for extraction, classification and recognition of features of SSVEP. A support vector machine and naive bayesian algorithm are adopted for extraction and recognition of OSP features. A recognition result is displayed on the screen in order to feed back to the subject. Then neat recognition is carried out. The mixing method for the brain-computer interface based on SSVEP and OSP has following advantages: rate of information transmission of the method for the brain-computer interface is increased based on SSVEP; and the method is easy in operation, few in electrode number and many in target number.

The present invention provides an electrode designed for implantation into the central nervous system (CNS) of a mammal, wherein said electrode is substantially coated with interleukin-1 receptor antagonist (IL-1ra) or a coating composition comprising it, and the IL-1ra actively inhibits scarring on or around the surface of the electrode when implanted into the CNS. The electrode of the invention may be used for brain recording and / or stimulation, and can thus be used for treatment of a brain dysfunction, a brain disease or disorder, or a brain injury, as well as for brain computer interface, brain machine interface, or electrotherapy.

Described herein are systems and methods for noninvasive functional brain imaging using low-coherence interferometry (e.g., for the purpose of creating a brain computer interface with higher spatiotemporal resolution). One variation of a system and method comprises optical interference components and techniques using a lock-in camera. The system comprises a light source and a processor configured to rapidly phase-shift the reference light beam across a pre-selected set of phase shifts or offsets, to store a set of interference patterns associated with each of these pre-selected phase shifts, and to process these stored interference patterns to compute an estimate of the number of photons traveling between a light source and the lock-in camera detector for which the path length falls within a user-defined path length range.

The present invention discloses an architecture of an embedded internet robot system controlled by brain waves, wherein the brain-computer interface and the internet robot system cooperate with the alertness level detection technology and the instruction translation technology, and thereby, the user can control a distal-end robot purely via consciousness activities and can interact with the environment as if there were an entity representing the user's consciousness appearing in the distal end. The seriously disabled person can regain his expressive ability via the present invention. Further, the present invention can also be applied to a multi-player interactive game system.

Disclosed herein is an adaptive brain-computer interface device. The brain-computer interface device includes a stimulus generation unit, a signal collection unit, a preprocessing unit, an analysis unit, and a stimuli sequence determination unit. The stimulus generation unit generates stimuli and applies the stimuli to a user. The signal collection unit records the user's Electroencephalogram (EEG) signals generated by the stimuli. The preprocessing unit extracts the feature of P300 on the basis of one of the stimulus from the EEG signals. The analysis unit determines whether P300 is present in the signal extracted by the preprocessing unit. The stimuli sequence determination unit determines the sequence of the stimuli of the stimulus generation unit by inferring a current state from the observations of the analysis unit and selecting an optimum stimulus for the current state.

The invention discloses a method for detecting a P300 electroencephalogram based on a convolutional neural network, which is used for a brain-computer interface classification algorithm and is capable of effectively solving a small sample problem in the conventional classification algorithm while improving the classification accuracy. Through using a thought of an image recognition field for reference, the method fully utilizes thoughts of a local receptive field and weight sharing of the convolutional neural network to take a typical P300 electroencephalogram acquisition sample as an analogy of a feature image, the sample characteristics are extracted through a continuous convolution process, and through carrying out feature mapping on a down sampling process, feature extraction and feature mapping are continuously performed, so that the sample characteristics are more simplified, meanwhile, through applying the local receptive field and weight sharing, network weighting parameters and computation complexity are greatly reduced to facilitate popularization of the algorithm. The experimental result shows that through the method adopted in the invention, the classification accuracy is effectively improved, the system stability is increased, and the method has better application prospect.

The invention discloses a brain computer interface mouse control-based Internet browsing method, which comprises the following steps of: initializing a system; controlling a mouse to move to a target area in a browser interface based on motor imagery and P300 electroencephalogram potentials; if a target is a text input target, switching the interface to a P300 text input interface, inputting characters by using P300 signal detection, returning to the browser interface after finishing inputting the characters and writing text input results into a selected text input box; and if the target is not the text input target, judging whether to click the target or not according to the motor imagery and P300 electroencephalogram potential information, clicking the target to open a new interface if determining to click the target, otherwise, controlling the mouse to continuously move in the interface. The brain computer interface mouse control-based Internet browsing method has the advantages of high control speed, high accuracy, good effect, working stability and capacity of realizing continuous control, and can be used under the condition of irremovability of a body or the computer mouse due to external or internal factors.

The invention discloses an upper limb rehabilitation training method based on a brain-computer interface and a virtual reality technology. A patient wears an electrode cap and a pair of VR glasses, and a computer, an EEG amplifier and a smartphone are connected; the computer judges whether the patient is trained for the first time or not; if yes, EEG signals are collected, individualized classifier calibration is performed, and then one training is started; otherwise, one training is directly started; in the training process, the pair of VR glasses and the smartphone construct an upper limb training action scene for a first-person perspective for the patient, the patient controls motions of the upper limb in a virtual scene in real time through continuous exercise imagination practice, an BCI module in the computer automatically adjusts the classifier according to the current training effect of the patient; after training is finished, the classifier of the BCI module performs self-adaptation adjustment for next training, it is ensured that training difficulty adapts to the patient functional recovery situation, data collection does not need to be performed before each rehabilitation training for calibration, and time is shortened.

The application provides a system and a method of cursor control based on a brain-computer interface. The system comprises a visual evoked simulation module, an electroencephalogram acquisition instrument and a processor, wherein the visual evoked simulation module is used for providing P300 evoked potential stimulation and SSVEP (Steady State Visual Evoked Potential) stimulation for a user in an interface display manner; the electroencephalogram acquisition instrument is used for acquiring the electroencephalogram signal of the user in real time and carrying out amplification and analog-to-digital conversion, and carrying out signal transmission through data wires and the processor; and the processor is used for receiving and processing the electroencephalogram signal, and judging the control purpose of the user and controlling cursor movement.

The invention relates to the technical field of medical instruments, and aims to provide a novel combined brain-computer interface normal form, which solves the technical difficult problem that two kinds of brain electrical signals are simultaneously evoked, separates the brain electrical signals in space and frequency domain and analyzes the signal features of the SSVEP and P300 so as to achieve the purpose of target identification. In order to achieve the purpose, the technical scheme adopted by the invention is that a combined brain-computer interface method based on the SSVEP and the P300 comprises the following steps: the SSVEP is evoked through line fixed frequency blinking, and the P300 is evoked through row color-frame highlighting; certain pre-processing is performed on the collected brain electrical signals, namely the SSVEP and P300; the lines in which the target characters are positioned are identified through analyzing the frequency features of the collected brain electrical signal SSVEP; the features of the P300 of the brain electrical signals are analyzed, the rows in which the target characters are positioned are identified. The combined brain-computer interface method and the combined brain-computer interface device are mainly applied to the brain-computer interface.

The invention discloses a tri-modal serial brain-computer interface method based on multi-information fusion. The method includes the steps: stimulating a testee by the aid of two visual stimulus paradigms; extracting electroencephalogram data of the testee; setting relevant parameters, reading the electroencephalogram data, preprocessing the electroencephalogram data, extracting characteristics, recognizing modes and acquiring final mode recognition results; converting the final mode recognition results into control instructions, and fulfilling specific tasks by executing the control instructions. A mixed-paradigm brain-computer interface introduces electrophysiology control signals except for electroencephalogram signals, and application environments and objects of the brain-computer interface are expanded to some extent. The tri-modal serial brain-computer interface method has the advantages of high stability, more options, wide application range and the like, and a foundation is laid for the brain-computer interface to step into a wide-range time application stage as soon as possible. The method can be used for fields such as electronic entertainment and industrial control, a perfect brain-computer interface system can be obtained, and the method is expected to obtain considerable social benefits and economic benefits.

The invention discloses a two-dimensional cursor control method and a two-dimensional cursor control device for a brain-computer interface. The method comprises that: a user generates a scalp electroencephalogram signal according to a working interface command in a display device; an electrode cap acquires the scalp electroencephalogram signal, and the scalp electroencephalogram signal is converted by an analog-to-digital conversion module and amplified by a signal amplifier and is transmitted to a computer; a signal processing module in the computer respectively preprocesses the transmitted signal, extracts characteristics of the transmitted signal and sorts the transmitted signal; and a control module in the computer converts the classified information into a control command to control a cursor to move on the display device. The device comprises the electrode cap, the signal amplifier, the computer and the display device; and a preprocessing module, a characteristic extraction module and a sorting algorithm module are respectively arranged inside the computer according to P300 information and motor imagery ERD / ERS information. The two-dimensional cursor control method and the two-dimensional cursor control device have the advantages of high control accuracy, good effect, stable work and capacity of realizing continuous two-dimensional motion of the cursor, and can be applied to motion control of a computer mouse, a wheel chair, a mechanical arm and the like.

The invention relates to a brain-computer interface short message sending control device and method. A brain-computer interface visual stimulator adopts a computer monitor to generate a pictorial stimulus signal in a programming way and is provided with a short message sender selection interface, a short message content selection interface and a confirmation cancelling interface for users to select. Visual stimulus adopts an instantaneous visual stimulus way and adopts a time sequence for same frequency compound stimulus. Signal processing comprises the following steps of: removing direct current of a brain electric signal, summarizing the average, carrying out lowpass filtering, judging a target watched by the testee through computing related coefficients between templates, and generating a brain-computer interface control signal. The sent mobile phone number and short message content can be obtained through a brain-computer interface test, and a control code is sent to a communication control module TC35, thus a short message is sent. The method provides a novel communication way for people who can not express ideal through actions of limbs and operate equipment.

The invention relates to the fields of numerical simulation, virtual reality, brain-computer interface, human-computer interaction, network communication, software development and the like. In order to construct a lifelike virtual reality simulation scene, real-time simulation data driving demonstration of a UAV cluster formation is carried out and human intervention to the simulation demonstration is realized through a plurality of human-computer interaction devices, so as to achieve the man-in-loop simulation effect. The invention discloses an unmanned aerial vehicle cluster formation interactive simulation verification system and an implementation method thereof. The system comprises a distributed real-time simulator, a host computer, a visual computer (client side), a display device and a human-computer interaction device. The simulator is formed by the target computer and responsible for running the real-time simulation program to simulate the UAV cluster formation. The host computer runs the server software. The visual computer runs the visual software developed on the base of Unity. The human-computer interaction device realizes human-computer interaction through visual software integration. The invention is mainly applied to the occasion of unmanned aerial vehicle simulation.