298 results about "Brain stimulation" patented technology

The delivery of neurostimulation to a subject using a closed-loop neurostimulation device (e.g., using a brain stimulation device to provide neurostimulation to a subject's brain) is controlled based on a global optimization-based temporal prediction framework. As a result, the brain stimulation device (e.g., a transcranial magnetic stimulation (“TMS”) device) is synchronized with the ongoing neural state (e.g., brain state) in real time. For instance, a brain recording is analyzed to extract the brain process of interest (e.g., frequency of brain oscillations) and used train a prediction algorithm. After that, a stimulation stage is implemented, in which the individual brain state is analyzed in real-time, the occurrence of the biomarkers (e.g., brain oscillation phase) is predicted, and the stimulation is triggered at the expected time.

The invention provides a nervous system closed-loop regulation and control system based on transcranial opto-acoustic cooperation. The nervous system closed-loop regulation and control system is composed of EEG monitoring equipment, personal information data, an opto-acoustic cooperation system, a multi-mode large model and a psychological disease database. Aiming at a transcranial infrared light and ultrasonic co-stimulation technology of a patient, through optimization of stimulation parameters, photoacoustic bidirectional regulation and control are realized, a multi-modal large model is used as a base, multi-modal data fusion and reinforcement learning are used as technical means, closed-loop photoacoustic co-stimulation system equipment is designed, and intervention parameters are automatically optimized; an effective regulation and control method for psychological diseases is realized through a non-intrusive brain stimulation technology, and adaptive adjustment and closed-loop feedback of parameters are realized. Brain waves of a patient are detected in real time, personal information of the patient is collected, the information is integrated and transmitted into the system after evaluation, intervention is adjusted in real time according to different brain states, and feedback is utilized to adjust parameters of next intervention and stimulate the precise regulation and control process.

Methods and devices for changing a brain state of a person from an initial brain state to a target brain state are described. The method comprises the following steps: receiving information representing the initial brain state, wherein the information comprises the structural composition and the functional architecture of the brain; estimating a likelihood of the brain changing from the initial brain state to the target brain state based at least in part on the received information; determining a non-invasive brain stimulation scheme based at least in part on the received information and the estimated likelihood of the brain changing from the initial brain state to the target brain state; and controlling at least one non-invasive brain stimulation device to stimulate the brain according to the non-invasive brain stimulation scheme. The method also includes using the brain information to provide information for a design to compute a generic artificial intelligence agent.

The present invention relates to an electrical nerve stimulator configured to deliver an electrical signal to a user to entrain Mu-band neural oscillations and / or Beta-band neural oscillations. The electrical nerve stimulator may be used in the treatment of neurological conditions associated with desynchronization of neural oscillations, such as Tourette's syndrome. The electrical nerve stimulator may be wearable on a wrist of a user, and may be configured to deliver rhythmic stimulation at a frequency falling within the same frequency range of Mu-band or Beta-band neural oscillations. The invention provides a convenient means of treating conditions such as Tourette's syndrome without the need for specialist medical equipment or facilities. Also disclosed is a method of delivering an electrical signal to a user to entrain Mu-band neural oscillations and / or Beta-band neural oscillations.

The invention relates to a three-dimensional spiral high-density neural electrode and a preparation method and application thereof. The three-dimensional spiral high-density neural electrode comprises a probe structure and a plurality of electrode sites. The probe structure is formed by curling a planar flexible electrode precursor, and at least one end of the probe structure is provided with a spiral outer surface of a three-dimensional spiral line structure. Electrode sites are distributed along a spiral path, have a size of 5-1000 [mu] m, and are used for contacting biological tissues. On the planar flexible electrode precursor, electrode sites are arranged on one or more straight lines forming an inclined angle alpha with the axial direction of the probe, and the spatial distribution is matched with the edge. Compared with the prior art, the method has the advantages that the constraint of a traditional wiring mode is broken through, the integration of high-density three-dimensional channels is realized under a micro size, and a new generation of solution is provided for a high-precision brain-computer interface, deep brain stimulation and a three-dimensional electroencephalogram.

Methods and apparatus for changing a brain state of a person from an initial brain state to a target brain state are described. The method includes receiving information characterizing the initial brain state, the information including a structural composition and a functional architecture of the brain, estimating based, at least in part, on the received information, a potential for the brain to change from the initial brain state to the target brain state, determining based, at least in part, on the received information and the estimated potential for the brain to change from the initial brain state to the target brain state, a non-invasive brain stimulation protocol, and controlling at least one non-invasive brain stimulation device to stimulate the brain according to the non-invasive brain stimulation protocol. The method also includes using brain information to inform the design of computational general artificial intelligence agents.

The invention provides a transcranial deep electrical stimulation closed-loop regulation and control system and method based on fNIRS dynamic guidance. The method comprises the steps that a transcranial alternating current electrical stimulation module applies an electrical signal to a target deep brain region according to preset parameters to carry out electrical stimulation regulation and control; the synchronous triggering module is used for realizing millisecond-level synchronization of a stimulation task and near-infrared brain function data acquisition; the brain function monitoring module analyzes the concentration change of cortex oxyhemoglobin in real time through the multi-channel head cap; the electrical stimulation-response coupling mapping module positions a significant activation channel by adopting statistical test, and establishes an oxyhemoglobin concentration variable and electrical stimulation current amplitude quantitative model; and the dynamic parameter adjusting module optimizes the output current in real time. Personalized closed-loop regulation and control of non-invasive deep brain stimulation can be achieved, cerebral cortex blood oxygen signals are monitored in real time through near-infrared brain function imaging, stimulation parameters are dynamically adjusted, and the accuracy and individualization level of deep brain stimulation are remarkably improved.

Provided herein are apparatuses, systems and methods for non-invasively assessing synaptic dysfunction in a patient with Alzheimer's Disease. Transcranial magnetic stimulation (TMS) is applied to at least one brain region of the patient. A plurality of TMS evoked potentials generated in response to the TMS applied to the at least one brain region of the patient is recorded with a plurality of electroencephalography (EEG) electrodes. At least one characteristic of the plurality of TMS evoked potentials is analyzed to assess synaptic dysfunction in the patient. An indication of the synaptic dysfunction assessment of the patient is output.

The embodiment of the invention discloses an electrode stimulation electric field simulation method and device, electronic equipment and a storage medium, and relates to the technical field of information, and the method comprises the steps: obtaining a brain image of a target user implanted with a stimulation electrode and an electrode implantation position of the stimulation electrode; performing brain tissue category division on the brain image to determine a first brain point cloud corresponding to the target user based on a brain tissue category division result; determining brain electrical characteristic distribution information corresponding to the target user based on a plurality of first data points in the first brain point cloud and the corresponding brain tissue electrical characteristic parameters; when the stimulation parameter is applied to the target contact of the stimulation electrode, the brain stimulation electric field distribution information corresponding to the stimulation parameter is determined based on the electrode implantation position, the brain electrical characteristic distribution information and the stimulation parameter, so that the reliability and the accuracy of the electrode stimulation electric field distribution information are improved; and the simulation efficiency and the real-time performance of the electric field distribution around the stimulating electrode are improved.

Devices, systems, software, and methods are provided for treating chronic pain in an individual using deep brain stimulation (DBS). An implantable brain stimulation and neural recording device is used to identify personalized pain biomarkers to automate brain stimulation using adaptive DBS algorithms in response to pain-associated brain states. Methods are also provided for identifying effective personalized brain stimulation sites for an individual through a systematic, multi-site brain mapping trial and tailoring real-time adaptive DBS programs to an individual to provide significant pain relief.

Devices, systems, software, and methods are provided for determining symptom severity of a subject having a movement disorder. The methods utilize video-based objective symptom quantification with classification of severity of symptoms using a machine learning algorithm. The subject methods can be used to diagnose and quantify motor symptom progression in patients with movement disorders such as Parkinson's disease, which is useful for assessing and optimizing therapeutic interventions, such as dopaminergic medications and deep brain stimulation (DBS).

The invention discloses a method for predicting the curative effect of brain stimulation on MCI based on a multi-modal image, and belongs to the technical field of medical data process.The method comprises the steps that through a multi-modal MRI feature fusion model, structure and functional MRI indexes are synchronously integrated, feature selection and dimension reduction are conducted through comparison between independent sample t test groups and LASSO regression, and the curative effect of brain stimulation on MCI is predicted; compared with the existing method, the method has the advantages that the obvious contribution of the change of the collaborative structure image index and the functional image index to the predicted curative effect is verified through the structure-function coupling analysis, and the prediction model is constructed, so that the prediction efficiency is improved. The contribution direction and strength of each image feature to curative effect prediction are analyzed and quantified in combination with SHAP values, feature weights are automatically optimized according to SHAP value distribution, and model high-contribution feature brain regions are revealed through SHAP so as to clarify curative effect biomarkers.

Devices, systems, software, and methods are provided for treating bradykinesia with deep brain stimulation (DBS). In particular, DBS is performed with a neural recording device that records brain electrical signals from neural activity associated with intended movement of the subject and automatically adjusts deep brain stimulator settings and / or delivers electrical stimulation to the brain when pre-specified patterns of neural activity associated with the intended movement are detected. Machine learning computational models are used to detect and classify patterns of neural activity associated with intended movement. The neural signatures of "intended movement" are used to assist with DBS programming to determine therapeutic stimulation parameters that boost movement when a patient starts to prepare for movement and during movements but stop when the patient is resting.

The invention discloses a control device and computer equipment for a brain health therapeutic apparatus, and relates to the technical field of brain stimulation control, and the method comprises the steps: synchronously collecting an fMRI activity map, sMRI data and whole-brain voxel-level DTI data of a subject, extracting a cortex target region to be stimulated, and reconstructing and generating a triangular mesh model; non-linear registration is carried out on whole-brain voxel-level DTI data and the sMRI space, and a target region vertex direction field is generated; calculating a direction field average direction and a direction field covariance of the direction field at the vertex of the target region; if the covariance of the direction field does not exceed a preset covariance threshold value, controlling the brain health therapeutic apparatus to perform magnetic stimulation operation on the cortex target region according to the average direction of the direction field; and if the direction field covariance exceeds a covariance threshold, screening a first target region vertex sector and a second target region vertex sector, and controlling the brain health therapeutic apparatus to perform time division multiplexing vector scanning between sectors. Therefore, the accuracy of targeted stimulation and the individual suitability are greatly improved.

A combined neuromodulation and / or neurostimulation system for mitigating locomotor deficits of / or neuronal disorders, especially Parkinson's disease, said system comprises: at least one Deep Brain Stimulation System for providing Deep Brain Stimulation to brain tissue of a subject, at least one control unit, configured and adapted to provide stimulation data, at least one stimulation unit, operatively connected to the at least one control unit, the at least one stimulation unit being configured and adapted to deliver epidural electrical stimulation to the dorsal side of the spinal cord of said subject, and at least one implantable pulse generator, wherein the at least one stimulation unit includes one or more electrodes configured to be implanted epidurally, the one or more electrodes being operatively connected to the at least one IPG.

A method of facilitating a skill learning process or improving performance of a task, comprising: determining a brainwave pattern reflecting neuronal activity of a skilled subject while engaged in a respective skill or task; processing the determined brainwave pattern with at least one automated processor; and subjecting a subject training in the respective skill or task to brain entrainment by a stimulus selected from the group consisting of one or more of a sensory excitation, a peripheral excitation, a transcranial excitation, and a deep brain stimulation, dependent on the processed temporal pattern extracted from brainwaves reflecting neuronal activity of the skilled subject.

Deep brain stimulation (DBS) can be used to treat many neurological conditions beyond traditional movement disorders. When patients do not suffer from traditional movement disorders, medical professionals cannot use traditional observation-based methods to configure the DBS system. A new method for selecting stimulation configurations can include recording internal data and external data as the patient performs (or attempts to perform) a motor task. The internal data is electrophysiology data recorded by a plurality of DBS electrodes, used to identify at least one of the plurality of electrodes closest to a neuronal population involved in control of the at least one motor task. The external data is electroencephalogram (EEG) data recorded by scalp electrodes, which is used to select at least one of the potential stimulation electrodes to deliver the DBS. When the electrode(s) delivering the DBS are selected, optimal parameters for the DBS are then chosen.

Methods and systems for analyzing and selecting therapy configurations for use in stimulating neural tissue. Probability shells relating to a likelihood that electrical stimulation issued to a given volume of neural tissue will cause a therapeutic outcome are integrated in a system for analyzing anatomical and other data, including lead position relative to neural anatomy. Metrics for analyzing therapy configurations can then be calculated, and the process of identifying likely beneficial therapy configurations is enhanced.

Systems and methods for configuring neurostimulation systems to identify optimal therapies for use in a patient. Positional data for a lead implanted in the patient and anatomical data are obtained. Non-linear response structures are identified in the patient, and therapy metrics are generated using non-linear functions of the quantity of volume segments in the non-linear response structures that would be activated by a given therapy configuration including a combination of current fractionalization and current amplitude.

Methods and systems for optimizing invasive and noninvasive brain stimulation are described herein. In a particular embodiment, methods and systems for a combinatorial, iterative approach to modify behavior are presented wherein deep brain stimulation (DBS) and other brain stimulation therapies are implemented in combination with monitoring the brain activity of an individual to optimize the effectiveness of the combinatorial approach to modify behavior. Methods described herein are iterative and systems described herein are utilized in iterative fashion. In a particular embodiment, modifying behavior provides a therapy for an individual in need thereof.

A headset for transcranial brain stimulation including: a forehead frame defining an elongated arch; a first electrode arranged at a first end portion of the forehead frame; a second electrode arranged at a second end portion of the forehead frame; a bracket arranged at a center portion of the forehead frame; and a circuit comprising the first and second electrodes and configured to be powered according to a schedule for performing the transcranial brain stimulation.

Systems and methods for adaptively controlling an electrical stimulation device, such as a closed-loop stimulation device, based in part on a Bayesian optimization of the operational parameters of the device are described. An adaptive dual control of the stimulation device can be provided. In a first control loop parameters are extracted from signals recorded from the subject by the stimulation device, and in a second control loop a Bayesian optimization is implemented with a hardware processor and memory to compute updated operational parameters for the stimulation device. As noted, the stimulation device is an electrical stimulation device, and may be a closed-loop stimulation device. Such devices can be used for deep brain stimulation (“DBS”), cardiac resynchronization therapy (“CRT”), and other electrophysiological stimulation applications.

The invention provides a deep brain stimulation method and system based on controllable current vectors of high-channel-number electrodes, and the method comprises the following steps: implanting two electrodes into a target region, and enabling a nucleus of the target region to be located between the two electrodes; by selecting different contacts on the stimulating electrodes, multiple channels of induced currents in different directions are generated in a plane constructed by the two electrodes; vector current is formed through vector superposition of the induction current of each channel, and the vector current acts on the target nuclei. The high-channel-number electrodes are adopted, programming control is carried out between the two electrodes, accurate control over current vectors is achieved, control over the magnitude and direction of target region nuclei stimulation current is accurately achieved through current vector superposition, therefore, a brain lesion area can be stimulated more accurately, meanwhile, the current vectors can be accurately controlled, and the stimulation effect of the brain lesion area is improved. And unnecessary current is prevented from diffusing to surrounding normal brain tissues, so that side effects caused by stimulation of a non-target area are reduced.

The invention relates to deep brain stimulation equipment capable of realizing an explosive stimulation mode, which comprises a deep brain stimulation unit and a deep brain stimulation electrode which are connected through an in-vivo lead. Wherein the deep brain stimulation unit is configured to enable a deep brain stimulation electrode to perform deep brain stimulation nerve regulation and control on a target spot in an explosive stimulation mode with adjustable stimulation parameters. Wherein one or more of group frequency, intra-group frequency and sine wave quantity in a single stimulation period can be adaptively adjusted by the deep brain stimulation unit according to different electrophysiological characteristics of a target point.

A headset for transcranial brain stimulation including: a forehead frame defining an elongated arch; a first electrode arranged at a first end portion of the forehead frame; a second electrode arranged at a second end portion of the forehead frame; a bracket arranged at a center portion of the forehead frame; and a circuit comprising the first and second electrodes and configured to be powered according to a schedule for performing the transcranial brain stimulation.

A method for treating a neuropsychiatric or neurological disorder by inducing neurological response in a subject, the method comprising: selecting a frequency for application of non-invasive brain stimulation to which a subject is to be exposed; exposing the subject to the non-invasive sensory stimulation at the selected frequency in a range of about 5-100 Hz.

The invention discloses an integrated multi-mode transcranial electrical stimulation and high-intensity deep brain stimulation device, and belongs to the field of neuromedical treatment, in the device, a main control module is used for receiving data sent by a serial port display screen communication module and processing and analyzing the data, and then a signal source module is driven to output a target signal; the signal source module selectively outputs a transcranial alternating current stimulation waveform, a time intervention electrical stimulation waveform, a high-current phase modulation time intervention electrical stimulation waveform, a transcranial pulse electrical stimulation waveform and a transcranial direct current stimulation waveform based on a plurality of waveform generators and digital potentiometers; and the signal amplification and constant current output module is used for amplifying the waveform voltage signal output by the signal source module, converting the waveform voltage signal into a constant current signal and outputting the constant current signal to the output module. According to the invention, the electric field intensity generated by the stimulation current at the deep brain target spot is improved, so that the deep brain region is effectively stimulated, and a more remarkable stimulation intervention effect is achieved.

A method includes receiving with a controller, neurophysiology activity data; receiving with the controller, biometric data for the patient; identifying with the controller, one or more weighted components of the neurophysiology activity data; assigning with the controller, based on the biometric data for the patient, a weight to each of the one or more weighted components; determining with the controller, based on a trained algorithm applied to the one or more weighted components, whether to apply the DBS; and instructing application with the controller, based on the determination, the DBS.

The invention relates to a non-invasive brain stimulation self-adaptive closed-loop regulation and control system. The system comprises a task interaction module which is configured to present a time sensing task to a target object and receive an interaction instruction of the target object; the non-invasive brain stimulation module is used for performing non-invasive brain stimulation; the sensing acquisition module is used for acquiring electroencephalogram data and behavioral data of a target object; the closed-loop regulation and control module comprises at least one block-level regulation and control primary unit, and each block-level regulation and control primary unit comprises a plurality of block-level regulation and control primary units; the trial secondary regulation and control primary unit is used for generating a first feature vector in real time on the basis of the currently collected electroencephalogram data and behavioral data so as to obtain a stimulation parameter of the next trial in the current block; the block-level regulation and control first-level unit is used for processing the currently collected electroencephalogram data and behavioral data to obtain a second feature vector, and based on the second feature vector, adaptive search is carried out under security constraints to obtain stimulation parameters of a next block. By adopting the method, the stability of the stimulation effect can be improved.

The invention discloses a brain stimulation reconstruction method based on visual experience retrieval, a medium and equipment, and relates to the technical field of computational vision, the method comprises the following steps: extracting low-level visual clues and high-level visual clues of a to-be-processed fMRI signal to ensure the retention of semantic information in a reconstruction process; by simulating the memory retrieval process of the human brain, the visual memory image is retrieved, context information is provided for degraded visual stimulation, the image reconstruction precision is further improved, and semantic details are enriched; a plurality of reconstructed images are generated by using low-level visual cues and super visual cues (a fusion result of high-level visual cues and CLIP features of visual memory images), and a final reconstructed image is selected from the reconstructed images, so that key semantic information in visual stimulation can be fully captured or reserved, and the accuracy of an image reconstruction result is improved.