17 results about "Cortex motor" patented technology

The invention provides a clinical motion control device, method and system, electronic equipment and a medium, and the device comprises an ultra-micro array implantation probe which is configured to be implanted into a brain motor cortex of a patient and collect a neuroelectric signal of the brain motor cortex; the integrated data processing module is electrically connected with the ultra-micro array implanted probe and is configured to convert the neuroelectric signals into digital signals and perform neural decoding on the digital signals to obtain motion control signals containing the motion intention of the patient; and the data transmission module is in communication connection with the integrated data processing module and is configured to transmit the motion control signal to external rehabilitation equipment through a wired interface or a wireless communication mode, so that the external rehabilitation equipment drives the limbs of the patient to execute corresponding rehabilitation motions. According to the invention, large-scale, high-precision and synchronous monitoring can be carried out on brain motor cortex neural activities, the signal acquisition quality is improved through an integrated structure design, and the signal decoding precision is improved at the same time.

The present application relates to the technical field of medical treatment, and in particular to a stimulation system for treating a tremor, and an action method and a stimulation parameter adjustment method. The stimulation system comprises: an execution part, which is used for applying to at least one target position of a human body a target stimulation action for treating a tremor; a collection part, which is used for collecting a movement state signal of at least one target position of the human body and collecting motor cortex electrocorticogram of the human body; and a control part, which generates target stimulation parameters on the basis of the movement state signal and the motor cortex electrocorticogram, and adjusts, on the basis of the target stimulation parameters, the target stimulation action for treating a tremor that is applied by the execution part. Therefore, the problems in the prior art, such as the effect of drug treatment being poor, a brain pacemaker surgery having a high risk, a high cost and a poor safety, and vibrating gloves treatment having poor comfort and user-friendliness and thus affecting normal daily life of patients, are solved.

A digital method of therapeutic brain stimulation is provided. The method comprises presenting to a user in a UI a group of trials by sequentially displaying symbols against a background. The symbols are randomly displayed one at a time against one several contexts in the background to stimulate the user's parietal or frontal lobes or motor cortex. A user response is received for each display of a symbol indicating whether the symbol is the same or different from an immediately prior symbol for the same context, wherein each trial has a maximum allowed response time for the user input after which any response is counted as a false alarm. A user score is generated for the group of trials, wherein the score compares correct identification and incorrect false alarm responses for the group of trials against a user score of a previous group of trials.

Provided herein are targeting peptides and vectors containing a sequence that encodes the targeting peptides that deliver agents to specific substructures in the brain. Specifically, the targeting peptide is a component of a modified, sequence-specified adeno-associated virus (AAV) capsid protein further wherein the brain substructure may be the globus pallidus, putamen, internal capsule, caudate, claustrum, substantial nigra, motor cortex, insula,.temporal cortex, thalamus, hippocampus, subiculum, and deep cerebellar nuclei.

A brain-computer interface (BCI) includes a multichannel stimulator and a decoder. The multichannel stimulator is operatively connected to deliver stimulation pulses to a functional electrical stimulation (FES) device to control delivery of FES to an anatomical region. The decoder is operatively connected to receive at least one neural signal from at least one electrode operatively connected with a motor cortex. The decoder controls the multichannel stimulator based on the received at least one neural signal. The decoder comprises a computer programmed to process the received at least one neural signal using a deep neural network. The decoder may include a long short-term memory (LSTM) layer outputting to a convolutional layer in turn outputting to at least one fully connected neural network layer. The decoder may be updated by unsupervised updating. The decoder may be extended to include additional functions by transfer learning.

The application relates to the technical field of brain-computer interface, and discloses a signal acquisition method for brain-computer interface control of a lower-limb exoskeleton robot. The method collects original electroencephalogram signals through a multi-channel electrode array arranged on a motor cortex of a scalp, and synchronously collects motion data of a lower-limb inertial measurement unit. In the signal processing process, differential amplification is adopted to suppress common-mode interference, adaptive narrow-band filtering is adopted to dynamically track electroencephalogram rhythms, and a blind source separation algorithm based on independent component analysis is adopted to remove motion artifacts. Finally, the processed motion intention electroencephalogram signals are output, the precision and real-time performance of intention recognition are improved, and accurate and stable control signals are provided for the lower-limb exoskeleton robot.

This invention relates to an instrument for treating neurological or psychiatric disorders using i-wave periodicity-dependent four-pulse theta burst stimulation (iQPS). The system includes a transcranial magnetic stimulation (TMS) stimulator configured to deliver test pulses to a target motor cortex region and therapeutic theta bursts to a treatment region, wherein the pulse frequency is customized according to the patient's individual i-wave periodicity. An electromyography (EMG) device records motor evoked potentials (MEPs) from the target muscles and analyzes the intervals between MEPs to determine the i-wave periodicity. Personalized stimulation enhances cortical plasticity by synchronizing stimulation with the brain's intrinsic neural timing. This invention is applicable to neurological and psychiatric conditions including depression, schizophrenia, stroke recovery, and neuropathic pain. Advantages include improved therapeutic efficacy, reduced patient response variability, and a non-invasive adaptive therapy model aligned with the patient's unique neurophysiological characteristics, thus providing a precise and scalable approach to brain stimulation.

A helmet with pre-positioned locations for transcranial magnetic stimulation (TMS) coils and sensors. The helmet has precision cut TMS coil guides for easy insertion and removal of the TMS coil. The helmet can have one or two TMS coil cut-outs positioned to enable inserted TMS coils to direct their generated magnetic waves to specific areas of a persons brain, including for example a dorsolateral prefrontal cortex, a motor cortex or a superior parietal lobule. The inner surface of the helmet can include at least one sensor array to detect levels of brain activity for neuroimaging. Different types of complementary sensing systems can be used at the same time. A helmet positioning system can be used to hold the helmet in place once the proper position has been determined, and can be manually or mechanically actuated such that one or more TMS coil modules are properly aligned over the targeted structure of the individual's head.

The present invention provides a method of treating or diagnosing an emotion or stress disorder comprising modulation of or detection of excitability of a motor cortex of a patient. The invention also provides a medicament for treating mood or stress disorders, wherein the medicament comprises a preparation for regulating the excitability of the motor cortex. The invention also provides a kit for diagnosing emotion or stress disorder. The invention also provides a medical device for treating or diagnosing mood or stress disorders.

This disclosure provides a method for selecting parameters for stimulation of the thalamus using a deep brain stimulator to treat a motor disorder in a subject, such as paralysis of the upper limb and face muscles. Also provided are methods for treating motor disorder in a subject. Also provided is an implantable electrode lead for neuromodulation and recording, configured to provide targeted stimulation and / or recording to multiple anatomically distinct neural structures, specifically the thalamus, the motor cortex, and optionally, the corona radiata, using a single continuous elongate lead body.

The invention relates to a mechanical arm self-adaptive grabbing system based on cortical neural signal and computer vision sharing and an implementation method of the mechanical arm self-adaptive grabbing system. The system comprises a sensing module used for collecting neural signals of a brain motor cortex through an intrusive microelectrode array brain-computer interface, identifying a macroscopic motion intention of a user, identifying a semantic category of a target object, and calculating a three-dimensional pose of the target object in a mechanical arm coordinate system; the shared control decision module is used for realizing automatic switching of control rights based on a finite-state machine and generating a mechanical arm motion track planning instruction and a manipulator grabbing gesture instruction; and the sharing control execution module is used for driving the mechanical arm to move to a target position according to the mechanical arm movement track planning instruction and controlling the mechanical arm to execute a self-adaptive grabbing gesture corresponding to the semantic category according to the mechanical arm grabbing gesture instruction. The intention of a brain-computer interface and the autonomous control ability of the mechanical arm can be fully fused, and the grabbing success rate and stability of the mechanical arm are improved.

The application discloses an olfactory training system for activating a motor-olfactory-hippocampal neural network and application, the system comprises a plurality of different odor sources, the odor source is used for alternating olfactory stimulation to stroke patients, so as to improve the cognitive function and / or olfactory function of the patient. The application firstly discloses that the function connection of the motor-olfactory-cognitive brain area is disordered after stroke, the function of the VIP neuron of the motor cortex (MO) around the infarction is inhibited; the VIP neuron of the MO region dominates the GABA neuron of the dorsal peripeduncular area (DP) through an inhibitory pathway, activating the pathway can remove the inhibition of the glutamatergic pyramidal neuron of the DP, enhance the excitatory input to the hippocampal CA3 region, and restore the olfaction and spatial memory. The application proves that the structured olfactory training can activate the loop, and significantly improve the cognitive function of the stroke patient. The application provides a simple and non-invasive stroke rehabilitation strategy.

This invention discloses a method for assessing motor cortical excitability based on threshold-tracking magnetic stimulation, relating to the field of biomedical engineering technology. The method includes the following steps: electrical stimulation of the median nerve in the subject's wrist; recording on the abductor pollicis brevis (APB) muscle; recording the stimulus-response curve; determining the cortical stimulus-response (SR) curve by increasing the magnetic stimulation intensity to the specified levels; calculating the statistical parameters of the mean and standard deviation of the excitability threshold; and determining the dynamic trend of cortical excitability. This invention determines the cortical stimulus-response curve by increasing the magnetic stimulation intensity to the specified levels, and calculates the central motor conduction time based on the stimulus-response curve using the F-wave method, thus completing the initial stimulus and threshold determination. Subsequent threshold tracking is then performed based on this technique, providing an efficient and accurate means of detecting motor cortical function for the diagnosis of neurological diseases.

The invention relates to the technical field of brain-computer interfaces, and provides a rehabilitation training method and system based on a mixed normal form brain-computer interface. The method comprises the steps that electroencephalogram signals of the prefrontal lobe or the motor cortex of a patient are collected; performing cooperative decoding on the electroencephalogram signals according to a preset mixed normal form decoding model, and identifying signal features; if the electroencephalogram signal is a prefrontal lobe electroencephalogram signal, the signal feature is whether to imagine an intention intensity score of walking and movement, and if the electroencephalogram signal is a motor cortex electroencephalogram signal, the signal feature is a motor imagery type and an intention intensity score of movement; generating a lower limb rehabilitation training instruction matched with the rehabilitation stage of the patient according to the signal characteristics, wherein the training instruction at least comprises any one of walking, knee bending, leg lifting, left leg lifting and right leg lifting; the training instruction is transmitted to an execution module of the rehabilitation robot, and the rehabilitation robot is driven to complete corresponding training actions.

The application relates to the technical field of brain-computer interfaces, and discloses an intelligent rehabilitation wheelchair based on a brain-computer interface and a control method thereof, wherein the method comprises the following steps: S1: collecting a first electroencephalogram signal of a user's motor cortex, pre-processing the first electroencephalogram signal, and obtaining a second electroencephalogram signal; S2: classifying the second electroencephalogram signal, decoding a wheelchair motion instruction, and calculating a cognitive load level according to the second electroencephalogram signal; and S3: generating a wheelchair speed parameter and a wheelchair turning radius according to the cognitive load level, and driving a wheelchair motor to perform a corresponding motion action based on the wheelchair motion instruction, the wheelchair speed parameter and the wheelchair turning radius. The method improves the motion intention decoding accuracy and reduces the decoding delay, and solves the problem of insufficient decoding performance caused by signal redundancy of a traditional model.

The invention discloses a non-invasive brain network nerve regulation and control system and a control method thereof. Magnetic resonance imaging / diffusion tensor imaging data of a testee are collected and processed, and double-target reliable positioning is carried out; determining an acoustic transducer channel layout and initial acoustic stimulation parameters according to the network model; transmitting a multi-channel multi-mode modulation acoustic stimulation signal, stimulating the cochlea to synchronously generate a multi-mode bioelectric pulse signal, and stimulating the cochlea to generate a multi-mode bioelectric pulse; synchronously or asynchronously acquiring feedback signals of different stages of EEG / EMG and extracting orbicular oculi muscle and cortex response characteristics; acoustic stimulation parameters of all channels are dynamically adjusted and optimized through a feedback algorithm, an acoustic stimulation parameter report is generated, cochlea and deep nuclei thalamus-ganglion-motor cortex loops are accurately excited and regulated to generate electrophysiological response through audible acoustic multi-mode stimulation, and the device has the advantages of being non-invasive, safe, adjustable in height, low in cost and the like.

The application provides a motor imagination training system based on a brain-computer interface, and relates to the technical field of intelligent control, and comprises: a rapid processing module, which is used for acquiring electroencephalogram signals when a training video is watched and performing time-frequency domain and spatial mode processing to obtain dynamic characteristics, and determining a target training video according to a mirror neuron activation probability in the dynamic characteristics; a fine processing module, which is used for acquiring multi-modal sensing signals when the target training video is watched to determine static characteristics of a brain motor cortex, the static characteristics including activation intensity of the brain motor cortex, connection intensity of inter-cortical functions and coupling intensity of nerves and muscles; and an adaptive adjustment module, which is used for adaptively adjusting at least one of an exoskeleton torque, a virtual reality task difficulty and a neural feedback sensitivity according to the activation intensity, the connection intensity and the coupling intensity. The application realizes individualized adaptation of training content and real-time dynamic closed-loop regulation and control of parameters, and improves the effect of individualized training.