140results about "Nervous system evaluation" patented technology

The invention discloses a nerve disease detection and analysis method and system, and the method comprises the steps: obtaining a bracelet collection signal, a sphygmomanometer collection signal, a movement behavior image and behavior test data, and extracting tremor intensity features, gait symmetry features and autonomic nerve rhythm features through multi-band decomposition of the bracelet collection signal; analyzing the motion behavior image and the standardized motion test to obtain a motion function score; carrying out heart rate variability analysis to identify a neural function abnormality mode; constructing a neural function state map and calculating a feature weight; predicting a disease progress trend in combination with historical monitoring data; and dynamically adjusting a prediction result through subsequent feedback correction information. Through a mode of combining short-time intensive monitoring and long-term intermittent acquisition, long-term trend prediction and dynamic correction based on initial data are realized, and the reliability and practicability of nerve disease risk assessment in a home scene are remarkably improved.

Systems, devices, and methods for neurostimulation using a combination of implantable and external devices to treat pain are disclosed.

The invention discloses a neural disease diagnosis system based on space-time attention and dynamic field self-adaption. The method belongs to the technical field of cross-modal medical data adaptive analysis. The technical problem that a brand new system capable of simultaneously fusing multi-modal information and modeling multi-scale spatial-temporal features and having dynamic field adaptive ability is urgently needed to improve the accuracy and generalization ability of intelligent diagnosis of multi-site nerve diseases is solved. The system comprises a data preprocessing module for extracting a standardized time sequence of a brain region from fMRI time sequence data; the two-channel feature coding network module obtains global features through an attention mechanism; according to the feature fusion and classification module, a main task classifier executes a main task and predicts whether a to-be-tested person suffers from nerve diseases or not, and a domain task classifier executes a domain task and predicts a site to which the to-be-tested person belongs; and the dynamic balance training module adjusts the dynamic balance of the main task and the domain task through a dynamic balance control strategy.

The invention relates to a device for risk assessment of nervous system diseases, and a processor of the device is configured to receive eye movement data and electroencephalogram data which are associated in a time sequence, and fuse a double-branch deep neural network in a model through multiple modes to assess the risk of the nervous system diseases, performing feature extraction and attention mechanism-based cross-modal feature fusion on the eye movement data and the electroencephalogram data to obtain cross fusion features; and outputting risk assessment results and risk assessment parameters of at least one type of nervous system diseases through an output layer of the multi-modal fusion assessment model. According to the method and the device, the problem that diagnosis sensitivity and universality are insufficient due to the fact that diagnosis only depends on a single information source in related technologies is solved, disease features can be more comprehensively constructed from two levels of neural activity and behavior response by fusing data of two modes of eye movement and electroencephalogram, parallel diagnosis is further performed for multiple types of diseases, and the diagnosis efficiency is improved. The sensitivity and applicability of neuropsychiatric diagnosis are improved, and particularly, the method has more remarkable accuracy in early stages such as mild cognitive impairment and the like.

The invention discloses a flexible hydrogel neural electrode and a preparation method and application thereof. The flexible hydrogel neural electrode comprises a flexible substrate layer, an electrode layer and a packaging layer which are sequentially arranged in a stacked mode, the flexible substrate layer and the packaging layer are each of a hydrogel fiber composite film structure formed by compounding a fiber film and hydrogel, and the fiber film is embedded in the hydrogel; the fiber film is a polycaprolactam fiber film, and the hydrogel is polyvinyl alcohol hydrogel; the electrode layer comprises a plurality of metal electrodes, and each metal electrode is provided with an electrode point and a bonding pad; the packaging layer is provided with a plurality of hole structures, and the holes are arranged corresponding to the electrode points and the bonding pads and enable the electrode points and the bonding pads to be exposed. The flexible hydrogel neural electrode provided by the invention has good biocompatibility, swelling resistance and process compatibility; meanwhile, the flexible hydrogel neural electrode can be stably applied to an implantable brain-computer interface and is used for realizing long-term stable acquisition and transmission of neural signals.

A computing device for enhancing communications is disclosed. The computing device includes a memory configured to store data, a video camera configured to receive video input data, and a microphone configured to receive audio input data. The computing device also includes a processor that is configured to analyze the received video input data, the received audio input data, and the data stored in the memory. The computing device further includes a visual display device that is configured to output a visual display based on the processor analysis, and a speaker output device that is configured to output an audio signal based on the processor analysis.

The invention discloses a nervous system function evaluation method and device, computer equipment and a medium, and relates to the technical field of intelligent medical treatment. The specific implementation mode comprises the following steps: acquiring sensor data of a plurality of body parts of daily activities of a user, wherein the sensor data is acquired through a sensor arranged in a home environment; obtaining a plurality of motion function evaluation parameters according to the sensor data; obtaining a nervous system function evaluation result based on the whole-age group normal population data model according to the multiple motion function evaluation parameters; and outputting a neurological function risk index and a risk index of the user according to a nervous system function evaluation result. According to the scheme, the nervous system function is evaluated by obtaining multiple evaluation parameters in daily life, and the accuracy and reliability of the evaluation result and the use flexibility of the evaluation method are improved.

The subject matter of the present disclosure generally relates to techniques for neuromodulation of a tissue that include applying energy (e.g., ultrasound energy) into the tissue to cause altered activity at a synapse between a neuron and a non-neuronal cell.

A neural stimulator system which generates stimulation from an implantable stimulator circuit which generates stimulation outputs which mimic biological signals. The user / operator can select stimulation generated from recorded waveforms, or by selecting the characteristics for generating stimulation based on randomized inter-pulse-intervals (IPI). A control unit controls the operation of the implantable stimulator circuit, and receives sets of stimulation parameters based on user input from a user input device executing application specific programming.

A system and method of collecting, analyzing, and assessing children's participation data in kindergarten activities is disclosed. The method divides a kindergarten setting into a plurality of zones assigned to a set of activities. Data on children's entrance and exit times for each zone, children's development level, children's interests and preferences are obtained from an RFID-based data collector comprising of one or more RFID tags that are embedded in bracelets or other wearable devices and are worn by one or more individual children, and one or more RFID readers that capture real-time data from the RFID tags associated with individual children, and a server that connects to the RFID readers to store and process data.

The invention relates to the technical field of rehabilitation physiological monitoring, and discloses a nerve-muscle recovery detection method based on HRV recovery rate and sEMG frequency spectrum declination, and the method comprises the steps: firstly obtaining an effective RR interval sequence subjected to quality gating and a steady state sEMG segment of a specific muscle group; then, extracting systemic HRV recovery features and local muscle fatigue features in parallel, and respectively generating a normalized HRV recovery rate score and a myoelectricity recovery score; through multi-level fusion, a global nerve recovery score, a local muscle recovery score array and a comprehensive nerve-muscle recovery score are integrated; and finally, based on the multi-dimensional evaluation results, generating personalized training suggestions. Therefore, the nerve-muscle system preparation degree of an individual can be comprehensively and accurately reflected, and a scientific basis is provided for optimizing a training plan and preventing sport injuries.

The invention discloses a neural signal decoding method, a brain-computer system, electronic equipment and a storage medium. The method comprises the following steps: acquiring a tested neural signal; determining the language state of the subject according to the neural signal and a preset language state detection model; determining a pre-trained language decoding model according to the language state; and decoding the neural signal by using the language decoding model to obtain a language decoding result. The technical problem that the neural signals corresponding to different language states cannot be decoded in real time when facing the neural signals corresponding to different language states is solved.

The invention relates to configuring a wearable device for a specific user. The wearable device couples to headwear to be worn by the specific user, and comprises an accelerometer to detect an acceleration change experienced by the user, and a notification component for providing a notification. The wearable device causes the notification component to provide the notification when the detected acceleration change exceeds a threshold acceleration. The invention comprises, at a mobile computing device, setting the threshold acceleration to be a standard threshold value, and monitoring input data indicative of at least one cognitive characteristic of the specific user. The invention involves updating the threshold acceleration to be a specific user threshold value, comprising adjusting the standard threshold value based on the monitored input data, and sending a control signal to control the wearable device to set the threshold acceleration to be the specific user threshold value.

The invention discloses an ADHD child food addiction neural mechanism evaluation method based on fMRI, and the evaluation method mainly comprises the following steps: obtaining the test results of the attention, execution function, intelligence quotient and food addiction of to-be-evaluated children, and dividing the to-be-evaluated children into an ADHD with food addiction group, an ADHD without food addiction group and a health control group according to the results; performing fMRI stimulation normal form execution after grouping, and performing brain function data acquisition; and finally, constructing a mathematical model of neural image data analysis, so that a specific neural circuit of ADHD children food addiction and a mechanism modulated by an emotional state can be revealed non-invasively and objectively, and an important scientific basis and tool are provided for early recognition, pathological mechanism research and targeted intervention strategy development of ADHD co-disease food addiction.

The invention discloses a nerve monitoring condensable and cuttable electrode and an electrocoagulation operation system. The nerve monitoring condensable and cuttable electrode comprises a handle shell, a condensable and cuttable high-frequency operation electrode assembly, a nerve detection electrode assembly and a driving control mechanism, wherein the condensable and cuttable high-frequency operation electrode assembly and the nerve detection electrode assembly are arranged in the handle shell. The driving control mechanism comprises an external operation part and an internal transmission assembly, and the external operation part is in transmission connection with the two electrode assemblies through the internal transmission assembly. When the external operating part moves towards a first direction, the high-frequency operation electrode assembly is driven to extend out and the nerve detection electrode assembly is synchronously driven to retract; otherwise, the nerve detection electrode assembly is driven to stretch out, and the high-frequency operation electrode assembly is synchronously driven to retract. Reverse linkage and physical mutual exclusion of the two electrodes are achieved through the internal transmission assembly, it is ensured that only one functional head is located at the working position at the same time, and the risk that due to the fact that the two electrodes stretch out at the same time, mutual interference of different energies and accidental touch of non-target tissue are possibly caused in the operation process is avoided.

A lateral retractor system for forming a pathway to a patient's intervertebral disc space includes a single dilator and a retractable dual-tapered-blade assembly. The dilator may feature a narrow rectangular body for insertion at an insertion orientation parallel to the fibers of the patient's psoas muscle, at an approximate 45-degree angle to the patient's spine. The retractable dual-tapered-blade assembly consists of only two blade subassemblies, each having a blade bordered by adjustable wings, along with built-in lighting and video capabilities. The dual-tapered-blade assembly may be passed over the single dilator at the insertion orientation and rotated approximately 45-50 degrees to a final rotated orientation parallel to the intervertebral disc space before the two blade subassemblies are retracted away from one another to create the surgical pathway, while simultaneously and continuously assessing for encroachment upon one or more nerve structures within 360-degrees of the instrument. Other embodiments are also disclosed.

The present invention relates to a system for early screening of autism spectrum disorder using eye tracking. According to the present invention, autism spectrum disorder may be diagnosed early by applying response data of a user's gaze, which reacts to images or videos outputted on a display, to an autism spectrum disorder screening model. In addition, the present invention may be used to easily check a degree of suspicion of autism spectrum disorder at home, and thus may be utilized in the fields of early diagnosis, prevention, and treatment of autism in children.

The application provides a neurovascular coupling imaging system, method, device and storage medium, which comprises an image collector, a microscope frame arranged in the light inlet direction of the image collector, a visible light system for emitting visible light to a sample to be collected after the visible light is reflected by a beam splitter in the microscope frame, a near-infrared light system for emitting near-infrared light to the sample to be collected after the near-infrared light is reflected by another beam splitter in the microscope frame, and a trigger device for switching the frequency of the time-sharing emission of each light source in the visible light system and the near-infrared light system based on the collection frequency of the image collector. The application can integrate different visible light or near-infrared laser light sources in the light path to be collected, is compatible with various imaging requirements such as visible light for imaging of nerve cell activity and near-infrared light speckle imaging for non-invasive blood flow imaging, ensures that there is no time difference between image collection and light source switching and no time resolution is lost, and facilitates subsequent storage and calculation of data.

The application provides a method for imaging-based diagnosis of neuropsychiatric lupus based on machine learning. The method comprises: obtaining a brain MRI image of a patient; segmenting the intracerebral region of interest of the preprocessed brain MRI image; extracting radiomics features in the region of interest; screening features related to the diagnosis and prediction of neuropsychiatric lupus; dividing the screened features into a first training set and a first test set; building N machine learning-based radiomics prediction models; saving the trained N machine learning-based radiomics prediction models; using multiple linear regression to save the radiomics prediction model corresponding to the optimal AUC brain region; obtaining the serological indicators of the NPSLE patient; dividing the serological indicators into a second training set and a second test set; building a joint prediction model combining radiomics features and serological indicators; and inputting the second test set into the joint prediction model to obtain the prediction classification result of the patient's neuropsychiatric lupus. The application fills the gap of magnetic resonance imaging in the diagnosis of NPSLE, and provides practical guidance for clinicians in assisting the diagnosis of NPSLE.

The application discloses a nerve monitoring coagulation and incision electrode and an electrocoagulation operation system. The nerve monitoring coagulation and incision electrode comprises a handle shell, a coagulation and incision high-frequency operation electrode assembly and a nerve detection electrode assembly arranged in the handle shell, and a driving control mechanism. The driving control mechanism comprises external operating parts and an internal transmission assembly. The external operating parts are respectively in transmission connection with the two electrode assemblies through the internal transmission assembly. When the external operating parts move in a first direction, the high-frequency operation electrode assembly is driven to extend and the nerve detection electrode assembly is synchronously driven to retract. Conversely, the nerve detection electrode assembly is driven to extend and the high-frequency operation electrode assembly is synchronously driven to retract. The application realizes reverse linkage and physical mutual exclusion of the two electrodes through the internal transmission assembly, ensures that only one functional head is in a working position at the same time, and avoids the risk of possible mutual interference of different energies and mis-touching of non-target tissues in the operation process caused by the extension of the two electrodes at the same time.

The invention discloses a multi-color multi-channel optical fiber stimulation and recording system optical path, and belongs to the technical field of neural signal recording, the multi-color multi-channel optical fiber stimulation and recording system optical path comprises an excitation optical path and an acquisition optical path, the excitation optical path comprises a plurality of excitation light generation assemblies, an optical coupling device, a collimation device, a deflection assembly, a dichroscope, an objective lens and an optical fiber assembly, and preferably, the optical coupling device is connected with the optical fiber assembly. The scattering sheet is arranged at the output end of the optical coupling device; the collection light path comprises the optical fiber assembly, the objective lens, a light splitting assembly, a focusing lens and a digital camera, and preferably, the collection light path further comprises a filter disc arranged between the light splitting assembly and the focusing lens. The exciting light generating assembly is composed of a laser light source and a light intensity adjusting device capable of independently adjusting the laser light source. Wave band expansion can be achieved without complex light path adjustment, the stability of the total output power of exciting light can be guaranteed, and fixed-point control over the light power can be achieved through the deflection assembly.

There is disclosed a system for monitoring one or more physiologic signals, autonomic neural signals, and / or electrophysiological signals from a subject, comprising: a head mounted display sized for placement onto a head of the subject comprising a visual input device and a back-facing imaging sensor; the visual input device arranged within a field of view of the subject when the head mounted display is coupled thereto, the visual input device configured to display an output image for the subject; the back-facing imaging sensor arranged with a field of view covering one or more facial features of the subject when the head mounted display is coupled thereto, the back-facing imaging sensor configured to generate one or more feedback images the subject; and a processor electrically coupled and / or wirelessly coupled to the visual input device and the back-facing imaging sensor, the processor configured to deliver the output images, accept the feedback images, and analyze the images to determine one or more of the physiologic, autonomic neural, and / or electrophysiological signals.

The application provides a neuromuscular coordination ability evaluation and training system with an environment simulation function, which introduces the movements of six degrees of freedom of the subject environment, such as up and down, left and right, and pitching, to simulate flight movements, so that the perception effect of the subject on the environment during the test and training process can be enhanced, and the result is closer to the result in the flight test; four degrees of freedom of the upper and lower limb interaction device and nine test paradigms are designed, the coordination test of two dimensions of coordination and reaction is involved, the test of multiple dimensions and indexes is involved, and the reliability and validity of the test can be improved; five single abilities of coordination ability and four single abilities of reaction ability are designed, the comprehensive ability of two dimensions is obtained through a weight coefficient, and all the results are recorded and managed; according to the daily record of the single abilities, targeted training tasks can be carried out, and the training efficiency is greatly improved; during the test process, the load can be parameterized and adjusted, and the difficulty of the test can be quantitatively controlled.

The invention provides an implanted sensor regulation and control data analysis method and system based on machine learning, relates to the technical field of implantation regulation and control application, and aims to enlarge a parameter search space, explore and apply a potential optimization scheme neglected in the past and effectively reduce the loss of a regulation and control effect by introducing an unbalanced associated reference optimization parameter group. Specifically, by comprehensively considering various balanced and unbalanced reference optimization parameter combinations, personalized regulation and control can be carried out for physiological characteristics and disease states of different patients, the treatment effect is remarkably improved, and a result of regulation and control optimization each time is taken as a training sample of machine learning, so that online learning and updating of machine learning are realized; according to the method, the prediction precision and generalization ability are continuously improved, so that the method can better adapt to the change of the physiological state of the patient, thereby providing a scientific and quantitative regulation and control optimization basis, improving the automation and intelligence level of the whole optimization process, and developing a new possibility for the application of implantable medical equipment.

Disclosed is a method of forming a conductive diamond layer on a surface of a carbon fibre substrate that is used as a component of an electrode for neural stimulation and / or electrochemical sensing. The method comprises functionalising at least a portion of the surface with a functionalising agent to facilitate coating the surface with the conductive diamond layer. The method also comprises providing a diamond precursor and depositing the diamond precursor over the functionalising agent to form the conductive diamond layer. The disclosure also relates to an electrode that is used as a component of an electrode for neural stimulation and / or electrochemical sensing.

A pulse generator system that facilitates asynchronous ignition of recruited neurons includes an implantable pulse generator (IPG) that is capable of sensing a degree of synchronous ignition of recruited neurons in tissue of a patient and modifying a stimulation procedure to facilitate asynchronism and reduce sensory abnormalities. An evoked composite action potential (ECAP) of the recruited neurons is sensed by the at least one non-active electrode as a measure of synchronism. An ECAP algorithm operable in the IPG evaluates the shape of the ECAP and determines one or more ECAP shape parameters that indicate whether the recruited neurons are a synchronous fire or a non-synchronous fire. If the shape parameter indicates significant synchronism, the ECAP algorithm may adjust the stimulation procedure to facilitate non-synchronous firing.

The invention discloses a sleep monitoring result determination method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a current state data set of a monitoring target and a current environment data set of an environment where the monitoring target is located; determining a current factor weight value of each piece of current state data in the current state data set according to the current environment data set, a historical sleep monitoring result of the monitoring target and a dynamic weight model; and determining a sleep monitoring result according to the weight value of each current factor and the attribution analysis model. By dynamically determining the weights of different state data, the sensitivity of each person to different environmental factors is better adapted, so that a more accurate sleep monitoring result is determined, the analysis accuracy of sleep influencing factors is improved, and the problem of misjudgment of a traditional fixed weight model under individual differences and complex scenes is solved.

A neural disease diagnosis system based on space-time attention and dynamic domain adaptation belongs to the technical field of cross-modal medical data adaptive analysis. It solves the technical problem that there is an urgent need for a new system that can simultaneously fuse multi-modal information, model multi-scale space-time features, and have dynamic domain adaptation capability to improve the accuracy and generalization ability of multi-site neural disease intelligent diagnosis. The system comprises: a data preprocessing module for extracting standardized time series of individual brain regions from fMRI time series data; a dual-channel feature encoding network module for obtaining global features through an attention mechanism; a feature fusion and classification module, wherein a main task classifier performs a main task to predict whether a testee has a neural disease, and a domain task classifier performs a domain task to predict the site to which the testee belongs; and a dynamic balance training module for adjusting the dynamic balance of the main task and the domain task through a dynamic balance control strategy.

The invention discloses a motion sickness detection and prediction model training method and a motion sickness detection and prediction method. The training method comprises the following steps: acquiring initial physiological signal training data and an initial motion sickness feedback sequence; the initial physiological signal training data comprises at least two initial physiological signal sequences, and the initial physiological signal sequences at least comprise a skin electric signal sequence, a heart rate sequence and a facial skin temperature sequence; performing first preprocessing operation on the initial physiological signal training data to obtain target physiological signal training data; performing second preprocessing operation on the initial motion sickness feedback sequence to obtain a target motion sickness feedback sequence; and performing feature extraction on the target physiological signal training data, and training the neural network model by using the extracted target feature sequence and the target motion sickness feedback sequence to obtain a motion sickness detection and prediction model. According to the embodiment of the invention, high-precision motion sickness detection and prediction are realized, and the user experience is improved.

Systems, devices, and techniques are described for analyzing evoked compound action potentials (ECAP) signals to assess the effect of a delivered electrical stimulation signal. In one example, a system includes processing circuitry configured to receive ECAP information representative of an ECAP signal sensed by sensing circuitry, and determine, based on the ECAP information, that the ECAP signal includes at least one of an N2 peak, P3 peak, or N3 peak. The processing circuitry may then control delivery of electrical stimulation based on at least one of the N2 peak, P3 peak, or N3 peak.