20 results about "Brain deep stimulation" patented technology

The invention discloses a deep brain targeted stimulation method based on a time-frequency interference technology, and relates to the technical field of nerve regulation, and an application system comprises a plurality of pairs of stimulation electrode modules, a data acquisition module, a data preprocessing module, a time-frequency interference stimulation signal generation module, a central control module and a data storage module. According to the method, a multi-azimuth surrounding layout of multiple pairs of stimulation electrodes is combined with a time-frequency interference technology, so that a high-frequency electric field forms constructive interference in a deep brain target area, and meanwhile, a frequency difference is dynamically adjusted based on different organism state requirements; and a closed-loop control system of data acquisition, preprocessing, state evaluation, parameter adjustment and stimulation application is constructed. The problems that a traditional deep brain stimulation technology is low in targeting precision, poor in state guiding efficiency and insufficient in stimulation system stability are solved, the energy focusing degree is improved to 90% or above, the sleep induction time is shortened to 20-30 minutes, and the method can be widely applied to nerve disease treatment and physiological state improvement.

A stimulation electric field display method, an apparatus, an electronic device, and a storage medium. The method comprises: in response to a model display operation, determining a target object and a brain tissue image model corresponding to the target object, wherein the brain tissue image model comprises at least one electrode model for deep brain stimulation (S110); in response to an electrode configuration operation, determining electrode configuration information and stimulation parameter application information of each electrode model (S120); and in response to an electric field display operation, determining program-controlled electric field information of the at least one electrode model under the electrode configuration information and the stimulation parameter application information, and displaying the program-controlled electric field information on the displayed brain tissue image model (S130).

The invention discloses a sleep state closed-loop deep brain stimulation method and system based on a multi-modal signal, and the method comprises the steps: preprocessing an obtained electroencephalogram signal and an electromyographic signal, extracting multi-dimensional candidate features, and obtaining a core feature vector through screening; constructing a sleep state prediction model, inputting the core feature vector into the sleep state prediction model, and outputting a probability result of sleep state classification and a corresponding reliability index; executing multi-level physiological safety verification to obtain a target state, and allowing to output a state switching instruction when and only when the multi-level physiological safety verification is passed and the target state meets a preset stable condition; and continuously outputting a corresponding stimulation parameter set to the deep brain stimulation electrode based on a final target state corresponding to the state switching instruction. The problems that in the prior art, in the closed-loop regulation and control process, the sleep state recognition result is excessively relied on, and physiological safety constraint and stimulation continuity control are lacked are solved.

Methods and systems for programming stimulation parameters for assisting deep brain stimulation (DBS) in experimental patients are described. A cumulative database includes data from multiple historical adaptation / programming sessions. The data may include various sets of stimulation parameters tried for patients in the database; data relating to the position of electrode leads relative to the anatomical features of the patient's brain, such as alignment with the subthalamic nucleus (STN); scores indicating the therapeutic effectiveness of the stimulation parameters; and data relating to stimulation field models (SFM) of the various sets of stimulation parameters. This database can be used to predict stimulation parameter sets that may be therapeutically effective for experimental patients.

A method for optimizing stimulation for a patient having a stimulator device, such as a deep brain stimulation (DBS) device, is disclosed that involves taking into account tissue imaging information in the environment around a lead. Test stimulation is provided at initial combinations of lead position and stimulation parameters, such as amplitude values, wherein the patient is scored for each combination. One or more objective criteria are measured and scored. The objective criteria may be electrode impedance and / or pressure indicators, such as cardiac signals. The process is iteratively repeated until a stop criterion is met. The lead position in question may be a longitudinal or rotational position about the lead, and if the lead is essentially oriented, preferably both.

A system for optimizing DBS parameters for a subject includes automatically performing actions via a processor. The actions include obtaining functional MRI data of a brain of the subject acquired utilizing an MRI system during DBS of the brain utilizing a first set of DBS parameters. The actions include generating functional MRI response maps from the functional MRI data. The actions include extracting, utilizing an unsupervised autoencoder-based neural network, features from the functional MRI response maps. The actions include determining, utilizing a deep learning-based DBS parameter classification model, whether the first set of DBS parameters are optimal DBS parameters for the subject based on the features. The actions include, when the first set of DBS parameters are not the optimal DBS parameters, predicting, utilizing a deep learning-based DBS parameter prediction model, a second set of DBS parameters that are the optimal DBS parameters for the subject based on the features.

Methods and systems are described for stimulation parameter programming to assist in deep brain stimulation (DBS) of a subject patient. The cumulative database includes data from a plurality of historical adaptation / programming sessions. The data may include various sets of stimulation parameters attempted for the patient in a database; data relating to the position of the electrode lead relative to an anatomical feature of the patient's brain, e.g., alignment with respect to its subthalamic nucleus (STN); a score of the stimulation parameter indicative of therapeutic effectiveness of the stimulation parameter and / or causing a side effect in the patient; and data relating to a stimulation field model (SFM) of the various sets of stimulation parameters. The database may be used to predict sets of stimulation parameters that may be effective or cause side effects to the treatment of the subject patient.

The invention relates to the technical field of medical electronics and artificial intelligence crossing, in particular to an implantable closed-loop deep brain nerve stimulation system and method with edge intelligence. The system comprises a core master control and functional circuit module, a pulse generation module, a deep brain electrode, a physiological signal acquisition module, a wireless communication module and a power management module. The core of the method is that a lightweight long-short-term memory network model is locally integrated and operated in an implantable device, electroencephalogram signals collected in real time are subjected to preprocessing and pathological state recognition, and the pathological states comprise multiple symptoms and different degrees of the symptoms; and according to the identified specific state, a corresponding electrical stimulation strategy is adaptively matched and executed to form closed-loop regulation and control. Real-time, accurate and personalized analysis of electroencephalogram signals is realized through edge intelligence, the technical problems that a traditional deep brain stimulation system depends on in-vitro equipment, response is delayed, and multiple symptoms and multiple degrees cannot be finely recognized are solved, and the effectiveness and safety of treatment are remarkably improved.

The invention relates to the technical field of deep brain stimulation, in particular to a deep brain electrical stimulation parameter intelligent optimization method for Parkinson patients. According to the method, feature measurement is carried out on neural residual signals in the deep brain stimulation process, waveform slope features and observation credibility are analyzed through the neural residual signals, and therefore an artifact form penalty term and path accumulation cost are determined; based on the path accumulation cost, a dynamic programming algorithm is adopted to obtain pathological signal estimation intensity, the pathological signal estimation intensity is utilized to perform characteristic measurement on the pathological outbreak density, and the stimulation pulse amplitude in the deep brain stimulation process is optimized based on the pathological outbreak density. According to the method, the intensity is estimated by measuring the pathological signals, the problem of signal fragmentation of the pathological signals is avoided, and therefore the stimulation pulse amplitude in the deep brain stimulation process is accurately optimized.

Methods and systems for analyzing and selecting therapy configurations for use in stimulating nervous tissue. A probabilistic shell related to the likelihood that electrical stimulation emanating to a given volume of nervous tissue will cause a therapeutic outcome is incorporated in a system for analyzing anatomical and other data, including lead location relative to the neuroanatomy. Metrics for analyzing therapy configurations may then be calculated and the process of identifying therapy configurations that may be beneficial may be enhanced.

The present application relates to the field of medical equipment, and particularly to a pulse generator and a control method thereof. The pulse generator of the present application uses the same pulse output circuit to send the same pulse output signal to the deep brain stimulation circuit and the vagus nerve stimulation circuit, so that the pulse generator can send the vagus nerve stimulation electrical signal to stimulate the vagus nerve and send the deep brain stimulation electrical signal to stimulate the deep brain. Since the deep brain stimulation electrical signal and the vagus nerve stimulation electrical signal are synchronously started based on the same pulse output signal, the two can be coordinated according to certain rules to achieve better therapeutic effect.

According to a deep brain stimulation device and a control method thereof according to one embodiment of the present invention, two electrodes are inserted into a deep brain nucleus and supplied with high-frequency current in order to treat brain and neural diseases such as Parkinson's disease, tremor, myodystonia, Alzheimer's dementia, epilepsy, obsessive compulsive disorder, depression, pain, drug addiction, and post-traumatic syndrome, wherein the two electrodes are not supplied with current at the same time, thus making it possible to extend the life of a battery while achieving treatment effects that are the same as or superior to the prior art.

Systems and methods for configuring a neurostimulation system to identify optimized therapy for a patient. Position data and anatomical data of a lead implanted within a patient are obtained. A non-linear response structure is identified within a patient, and a therapy metric is generated using a non-linear function of the number of volume segments in the non-linear response structure, which is to be activated by a given therapy configuration that includes a combination of current subdivision and current amplitude.

The present application relates to a kind of brain deep electric stimulation equipment capable of realizing burst stimulation mode, the electric stimulation equipment includes brain deep stimulation unit and brain deep stimulation electrode, and they are connected by in-vivo lead wire.Wherein, brain deep stimulation unit is configured to be able to make brain deep stimulation electrode at adjustable stimulation parameter burst stimulation mode to implement the deep brain stimulation neuroregulation of target target point.Therein, the stimulation signal of burst stimulation mode can be adaptively adjusted according to the different electrophysiological characteristics of target target point one or more of group frequency, intra-group frequency and the number of sine waves in single stimulation period.

Systems and methods for providing evoked response guided multi-site deep brain stimulation (DSB) at various brain targets are disclosed. An exemplary system includes at least one multi-electrode lead, an electrical stimulator to provide electrical stimulation to a neural target, a sensing circuit to sense an evoked response (ER) to the electrical stimulation, and a controller circuit. In response to electrical stimulation of the first neural target in accordance with the first stimulation setting, the controller circuit collects the ER from the first sensing location and determines or adjusts a second stimulation setting for stimulating the second neural target based on the sensed ER at the first neural target. The second neural target may be stimulated according to the second stimulation setting to modulate the ER of the electrical stimulation at the first neural target and produce a desired therapeutic outcome in the patient.

A lead for deep brain stimulation, a stimulation apparatus, and the use of the apparatus. The lead is configured to stimulate two or more intracerebral functional targets. The lead is directionally implanted into the brain, passing through or being inserted into the two or more intracerebral functional targets to apply joint electrical stimulation to the two or more intracerebral functional targets. The lead comprises a stimulation section (1), wherein the stimulation section (1) is provided with a lead contact combination (4) arranged in the length direction of the stimulation section (1), the lead contact combination (4) comprises at least two lead contact groups (41), the at least two lead contact groups (41) respectively correspond to different intracerebral functional targets, each lead contact group (41) comprises at least one lead contact (10), at least one lead contact (10) in the same lead contact group (41) can output the same electrical stimulation parameter combination, and electrical stimulation parameter combinations output by different lead contact groups (41) are different.

The application discloses an ultrasonic-electroencephalogram multifunctional electrode for deep brain stimulation, which comprises a base microtube, a PMUT electrode for deep brain ultrasonic stimulation and a SEEG electrode for electroencephalogram signal detection from inside to outside. The ultrasonic-electroencephalogram multifunctional electrode for deep brain stimulation has the functions of fixed-point ultrasonic nerve stimulation and in-situ electroencephalogram signal detection, provides strong support for future closed-loop nerve stimulation, and has the advantages of simple preparation process and low manufacturing cost.

The invention discloses a closed-loop multi-device cooperative electrical stimulation system, which comprises an implantable deep brain stimulation sensing device, wherein the implantable deep brain stimulation sensing device collects multiple paths of electroencephalogram signals at multiple positions of the brain of a user and transmits the electroencephalogram signals to a user intention recognition model; the myoelectricity acquisition device acquires a user leg myoelectricity signal and transmits the user leg myoelectricity signal to the user myoelectricity identification model; the user intention recognition model recognizes and obtains a user stepping intention according to the electroencephalogram signal; the user myoelectricity recognition model carries out recognition according to the user leg myoelectricity signals to obtain user leg muscle actions; the in-vitro program controller controls the implantable deep brain stimulation sensing device and the leg physiotherapy electrode device to electrically stimulate the deep brain and the legs of the user according to the stepping intention of the user and the leg muscle actions of the user. According to the closed-loop multi-device cooperative electrical stimulation system, frozen gait moments can be accurately recognized, synchronous pulse electrical stimulation is carried out on deep brain parts and leg muscles, the stimulation effectiveness and safety are ensured through closed-loop parameter adaptive adjustment, and frozen gaits are cracked in a more intelligent and more accurate mode.

This disclosure provides a method for optimizing surgical placement of stimulation leads within the thalamus to treat a motor disorder in a subject, such as paralysis of the upper-limb and face muscles, which cause speech motor deficits. Also provided are methods for treating motor disorders in a subject.

Methods and systems are described for assisting in programming stimulation parameters for deep brain stimulation (DBS) of a subject patient. A cumulative database records a set of stimulation parameters used in a programming session for a plurality of patients and associates the set of parameters with good treatment outcomes and / or side effects. The cumulative database also includes a stimulus field model (SFM) for the set of parameters. The overlap of the SFM for the set of parameters may be associated with a therapeutic effect and used to determine a target volume and / or an avoidance volume for stimulation of the subject patient. In some embodiments, the SFMs may be weighted to de-emphasize the volume near the electrode leads.