277results about "Nervous system evaluation" patented technology

The invention provides a limb nerve rehabilitation state evaluation method based on multi-modal sensor data fusion. Motion inertia data, electromyographic signal data and text data of a corresponding limb nerve rehabilitation action manual of a patient during rehabilitation actions are obtained in real time; inputting the data into a designed and trained multi-modal data feature extraction network to obtain motion inertial data features, electromyographic signal data features and text semantic features; inputting the motion inertia data features, the electromyographic signal data features and the text semantic features into a designed and trained multi-modal data feature fusion network to obtain multi-modal fusion features; and inputting the multi-modal fusion features into a trained prediction output network to obtain a limb nerve rehabilitation state prediction value of the patient. Through multi-modal data fusion and time-dependent feature extraction, the limb nerve rehabilitation state of the patient is evaluated more accurately, and a more reliable diagnosis basis is provided for doctors. Meanwhile, the labor cost is reduced and the evaluation efficiency is improved.

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.

Disclosed herein are systems and methods for electrically modulating tissue. Systems can include a current generator; at least one implantable working electrode, the at least one implantable working electrode configured to be in electrical communication with the current generator; at least one indifferent electrode; and a controller configured to signal the current generator to: generate a set of currents with a set of initial polarities to be delivered to the working electrodes; and wherein the at least one indifferent electrode absorbs a bias current which is equal in magnitude and opposite in polarity to a summation of the set of currents.

The embodiment of the invention provides a physiological data waveform display method and device, electronic equipment and a storage medium. The physiological data waveform display method comprises the following steps: respectively acquiring first down-sampling data corresponding to physiological data which is sampled by a plurality of sampling channels and is subjected to first down-sampling processing; displaying a first waveform of each sampling channel according to the first down-sampling data; in response to a selection operation of a user on the first waveform of the target channel, obtaining original physiological data of the target channel before the first down-sampling processing; second down-sampling processing is carried out on the original physiological data to obtain second down-sampling data, and the down-sampling mode of the second down-sampling processing is different from that of the first down-sampling processing; and displaying a second waveform of the target channel according to the second down-sampling data. Through dynamic combination of the first down-sampling processing and the second down-sampling processing, global features of the physiological data can be displayed, local features of the physiological data can be clearly displayed, and the accuracy of physiological data analysis and monitoring is improved.

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

The invention relates to an animal craniocerebral injury model construction method and system, and the method comprises the following steps: 1, selecting a plurality of healthy male SD (Sprague Dawley) rats, breeding the rats in different cages in a 12-hour illumination environment and a 6-hour dark environment at the temperature of 25 DEG C, dividing the rats into three groups, and enabling the rats to eat and drink water; 2, the rats are divided into an X group, a Y group and a Z group through random grouping, the X group is a mild craniocerebral injury group, the Y group is a moderate craniocerebral injury group, the Z group is a severe craniocerebral injury group, and the number of the rats in each group is equal; according to the animal craniocerebral injury model, animal craniocerebral injury of different degrees can be simulated, the injury degree can be evaluated, and the model has good repeatability, reliability and stability and has good reference value in practical application.

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.

Assemblies, systems, and methods are directed at a neuromonitoring bone drill bit. The assembly may include a surgical bone drill bit, a neuromonitoring connection in electrical communication with the drill bit, and a shield extending over a distal end of the drill bit. The shield may be configured to withdraw proximally as the drill bit is advanced into a subject's bone. The assembly may be connected to a surgical drill and used in a surgical spinal procedure. In operation, the assembly may be advanced to a subject's bone at a surgical site and the drill bit may rotate into the subject's bone. In response, the shield may engage the bone and the drill bit may be advanced with respect to the shield. The shield may electrically insulate tissue from electrical current passing through the drill bit as it is inserted at the surgical site.

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 sensory nerve quantitative detection method and system based on electroencephalogram characteristics, and relates to the technical field of electroencephalogram measurement, and the method comprises the steps: building detection files in one-to-one correspondence with users; respectively wearing the current stimulation module and the electroencephalogram detection module on the wrist and the head of the user; current stimulation is applied to a user step by step through a current stimulation module, and gamma waves in electroencephalogram signals of the user are collected in real time through an electroencephalogram detection module; gamma waves in the electroencephalogram signals of the user are analyzed, and whether the intensity of current applied to the user by the current stimulation module exceeds a physical stimulation sensing threshold value of the subject or not is judged; and analyzing severity grades of sensory disorders. The method has the advantages that detection is carried out through brain wave signals without relying on subjective feedback of a patient, interference of factors such as emotion and psychology is avoided, and even a special patient who cannot carry out self-perception report can complete sensory nerve quantitative detection through objective physiological reaction of brain waves.

The invention relates to the field of neuroscience experiments, and discloses a method for accurately adjusting the precision of targeted light and calibrating neuron sampling images, which comprises the following steps of: 1, acquiring image data containing neuron activity information; step 2, preprocessing the image data to remove artifact noise; step 3, modeling the deformation of the nervous tissue based on the image data; step 4, regulating and controlling optical system parameters for targeted light stimulation according to a deformation modeling result; and 5, closed-loop updating is performed on the modeling result and the regulation and control parameters based on feedback image data, the image data in the step 1 comprises a calcium imaging image and a targeted light feedback image which are synchronously acquired, the calcium imaging image is used for reflecting neuron activity, and the targeted light feedback image is used for calibrating a light spot position. By adopting an accurate calcium imaging technology and a targeted light feedback image synchronous acquisition scheme, real-time synchronization of neuron activity and light spot position is realized.

The invention relates to the technical field of health risk assessment, in particular to a neurosurgery risk prediction method and system based on big data analysis, and the method comprises the steps: obtaining the neural signal intensity of a brain region in preoperative functional image data of a patient, analyzing the balance degree of neural signal transmission, and analyzing the balance of oxygen metabolism distribution according to the nerve conduction rate. And preoperative nerve state information is formed. According to the method, by accurately extracting the preoperative neural activity signals and analyzing the signal transmission delay, the fluctuation amplitude and the oxygen metabolism balance, the accuracy of individual neural function state evaluation is improved. In the postoperative recovery stage, the abnormal region is dynamically recognized in combination with the neural signal change trend, and the metabolism matching capacity is evaluated, so that the recovery mode is more refined. Neural network connection adjustment capability analysis enhances signal transmission stability evaluation, and abnormal region identification accuracy is improved by combining time deviation and oxygen metabolism recovery consistency.

At least partial function of a human limb is restored by surgically removing at least a portion of an injured or diseased human limb from a surgical site of an individual and transplanting a selected muscle into the remaining biological body of the individual, followed by contacting the transplanted selected muscle, or an associated nerve, with an electrode, to thereby control a device, such as a prosthetic limb, linked to the electrode. Simulating proprioceptive sensory feedback from a device includes mechanically linking at least one pair of agonist and antagonist muscles, wherein a nerve innervates each muscle, and supporting each pair with a support, whereby contraction of the agonist muscle of each pair will cause extension of the paired antagonist muscle. An electrode is implanted in a muscle of each pair and electrically connected to a motor controller of the device, thereby simulating proprioceptive sensory feedback from the device.

The invention discloses a thyroid recurrent laryngeal nerve simulation marking system, particularly relates to the field of recurrent laryngeal nerve simulation prompting and marking, and comprises a data input layer, a data processing layer and a data output layer, the data input layer comprises an electrical stimulation module and a signal acquisition module; the data input layer is used for transmitting stimulation data and biological signals to the data processing layer; the data processing layer comprises a central control module; the data processing layer is used for outputting an analysis result to the data output layer; and the data output layer comprises a positioning prompt module and a display and interaction module. Through the multi-pole electrode array and the tissue conductivity measuring unit, in combination with a dynamic current distribution technology, stimulation of a target nerve area is realized; meanwhile, the feedback control unit adjusts stimulation data according to dynamic changes of the nerve response signals, a closed-loop optimization mechanism is formed, and therefore the problem that stimulation is not uniform due to individual tissue differences of patients is effectively solved.

The invention provides a cranial nerve fatigue assessment method and device, equipment and a medium, and relates to the technical field of smart medical treatment, and the specific implementation mode comprises the steps: collecting multi-dimensional eyeball movement features of an assessment object in the process of performing visual guidance on the assessment object to execute a plurality of eye movement tests, the multi-dimensional eyeball activity features are controlled and realized by different functional structures of the brain; the multi-dimensional eyeball movement features are input into a fatigue assessment neural network model, the neural network model outputs a cranial nerve fatigue assessment value, and the fatigue assessment neural network model is a neural network model constructed based on a mesh mapping relation of the eyeball movement feature-brain structure-fatigue performance. The fatigue manifestation is a change condition of eye movement activity characteristics during cranial nerve fatigue. According to the method, the problems of low efficiency, single evaluation dimension, one-sided judgment basis and the like of an existing fatigue evaluation method are solved, the evaluation accuracy and reliability are improved, and comprehensive, systematic and efficient fatigue monitoring is realized.

The invention relates to the technical field of data processing, in particular to a construction method and system for a neural rehabilitation evaluation model. The method comprises the following steps: acquiring multi-modal data of a neurological rehabilitation patient; performing feature extraction according to the multi-modal data of the neurological rehabilitation patient to obtain multi-modal feature data of the neurological rehabilitation patient; performing data classification on the multi-modal feature data of the neurological rehabilitation patient to obtain multi-modal feature classification data; and marking the multi-modal feature data of the neurological rehabilitation patient by using the multi-modal feature classification data to obtain multi-modal feature marking data of the neurological rehabilitation patient so as to carry out neurological rehabilitation evaluation model construction auxiliary work. According to the method, the model capable of comprehensively and objectively evaluating the rehabilitation progress of the neurological rehabilitation patient is constructed in an auxiliary manner, so that a scientific basis is provided for rehabilitation treatment.

Systems and methods are disclosed that facilitate providing guidance to a user during performance of a program or routine using a personalized avatar. In an aspect, a system includes a reception component configured to receive biochemical information about a physiological state or condition of a user, including information identifying a presence or a status of one or more biomarkers. The system further includes an analysis component configured to determine or infer one or more characteristics of the physiological state or condition of the user based on the information identifying the presence or the status of the one or more biomarkers, and a visualization component configured to adapt an appearance of an avatar presented to the user based on the one or more characteristics to reflect the one or more characteristics.

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.

Assemblies, systems, and methods are directed at a neuromonitoring bone drill bit. The assembly may include a surgical bone drill bit, a neuromonitoring connection in electrical communication with the drill bit, and a shield extending over a distal end of the drill bit. The shield may be configured to withdraw proximally as the drill bit is advanced into a subject's bone. The assembly may be connected to a surgical drill and used in a surgical spinal procedure. In operation, the assembly may be advanced to a subject's bone at a surgical site and the drill bit may rotate into the subject's bone. In response, the shield may engage the bone and the drill bit may be advanced with respect to the shield. The shield may electrically insulate tissue from electrical current passing through the drill bit as it is inserted at the surgical site.

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.

The embodiment of the invention provides an image recognition and micro-current detection method and system for intercostal nerve plexus avoidance, and belongs to the technical field of data processing. The method comprises the steps of collecting initial image information corresponding to a first target object, and performing edge detection on the initial image information to obtain a corresponding target recognition result; determining a corresponding current parameter during micro-current detection, and obtaining a corresponding reaction potential signal of a related area of the first target object under the current parameter; performing nerve classification according to the reaction potential information to obtain a target nerve type corresponding to the related area; aligning the related area with the initial image information to obtain a target alignment result, and determining related edge information corresponding to the related area according to the target alignment result and the target recognition result; and generating intercostal nerve plexus avoidance information according to the target nerve type and the related edge information, and displaying the intercostal nerve plexus avoidance information to a second target object.

The invention discloses an analog front-end system based on a nano-enzyme microelectrode and a detection method. The system comprises a nano-enzyme microelectrode array, an electrophysiology acquisition module, an electrochemical acquisition module and a control module, the electrochemical acquisition module is used for acquiring electrochemical signals, and the control module is used for receiving and processing the electrochemical signals in an electrochemical acquisition mode; the nano-enzyme microelectrode array is used for being in contact with limbs of a detected object so as to collect electromyographic signals; the control module is used for receiving and processing the electromyographic signals in an electrophysiological acquisition mode, and determining the electrophysiological signals through the electromyographic signals; and the control module is also used for switching acquisition modes. According to the embodiment of the invention, the accuracy of the analog front-end circuit system in the aspect of neural signal acquisition can be improved; meanwhile, through a multi-module integration mode, the size of the system is reduced. The method can be widely applied to the technical field of electrochemical signal detection.

The invention discloses an eye movement data processing method and system for autism spectrum disorder detection, a plurality of detection icons in a detection task are displayed according to different movement rules, the moving detection icons guide a testee to watch a display module, then an eye movement image sequence of the testee watching the detection icons is collected, and the eye movement image sequence of the testee watching the detection icons is displayed according to the collected eye movement image sequence. Extracting eye movement data from the detection icons, grouping the eye movement data, calculating a sight line drop point displacement data set corresponding to each group of eye movement data, importing a motion function corresponding to each detection icon into a test coordinate system, and respectively importing each sight line drop point displacement data set into the test coordinate system; and judging which motion function each sight line drop point displacement data set accords with, thereby dynamically associating the sight line position of the testee with the detection icon, and realizing the rule capture of the sight line of the testee following the detection icon. The detection mode does not need to be matched with high-precision and high-cost hardware for use, the universality is improved, and a large-range and rapid-detection screening scene can be met.

Systems, devices, and techniques are described for determining stimulation parameters based on one or more stimulation thresholds (e.g., a perception threshold or a detection threshold). In one example, a medical device includes sensing circuitry configured to sense one or more ECAP signals, wherein the sensing circuitry is configured to sense each ECAP signal of the one or more ECAPs elicited by a respective control pulse of a plurality of control pulses, and the medical device includes processing circuitry configured to determine, based on the one or more ECAP signals, a stimulation level for the plurality of control pulses that achieves a stimulation threshold, determine, based on the stimulation level, a value of a stimulation parameter that at least partially defines a plurality of therapy pulses of electrical stimulation therapy, and control stimulation generation circuitry to deliver the electrical stimulation therapy according to the value of the stimulation parameter.

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.

A radiofrequency ablation electrode needle with multi-dimensional nerve monitoring, comprising a nerve monitoring flexible electrode, a radiofrequency thermocoagulation electrode, and three knob modules for adjusting the angle of the nerve monitoring flexible electrode. The X-axis rotation knob, Y-axis rotation knob, and Z-axis telescopic knob are respectively arranged on a triangular fixing seat. The X-axis rotation knob, Y-axis rotation knob, and Z-axis telescopic knob are respectively connected to the nerve monitoring flexible electrode through control cables. The front end of the triangular fixing seat is fixedly connected to the radiofrequency thermocoagulation electrode, and the rear end is docked with a cable. Compared with the prior art, the multi-dimensionally extendable electrode head of the present invention penetrates from the head end of the radiofrequency thermocoagulation electrode, and can achieve deflection in the front, back, left, and right directions in the X / Y directions and telescoping in the Z direction. The detection position of the flexible electrode head can be controlled by the X / Y / Z knobs. The monitoring electrode of the present invention can comprehensively monitor the ablated nerve lesion part, and to a certain extent, avoid the problems of incomplete nerve destruction or excessive nerve destruction.

The invention discloses a novel monitoring and intervention system for parathyroid gland function protection in a thyroid cancer operation, which comprises a nerve monitoring module, a measurement module, a light regulation and control module, an index monitoring module, a data regulation and control module, an intelligent feedback module and a postoperative monitoring module, comprising parathyroid gland specific fluorescent dye and a near-infrared light imaging system and is used for visualizing parathyroid glands in real time during an operation, and the measuring module is used for measuring the concentration value of calcium ions in a measured solution in real time and uploading the concentration value to the system to be stored and collected; blood circulation index data, lactic acid level data and peripheral perfusion parameters are collected through the index monitoring module, the accuracy and diversity of data collection in the operation process are improved, real-time field data collection is conducted on an operation site, and related blood circulation state data are collected through the measurement module and the light regulation and control module.