716 results about "Neurology speciality" patented technology

The invention discloses a neurology nursing potential safety hazard monitoring system and method, and relates to the technical field of medical information safety monitoring, and the system comprises a first collection processing unit which is used for collecting monitoring data of a target patient, inputting the monitoring data into a time sequence deep network for processing, and obtaining risk feature data; the second collecting and processing unit is used for collecting physiological state data of the target patient, constructing a risk assessment rule base based on a medical knowledge graph to analyze the physiological state data, and generating risk probability data; and the risk early warning unit is used for inputting the risk feature data and the risk probability data into a Bayesian fusion network, generating risk early warning information and sending the risk early warning information to the medical care terminal. According to the invention, collaborative analysis of multi-source information is realized through the Bayesian fusion network, the problem of low early warning accuracy of a traditional single monitoring method is solved, and the reliability of potential safety hazard monitoring is improved.

The invention provides a neurology clinical nursing potential safety hazard analysis method and device, and relates to the technical field of neurology clinical nursing, and the method comprises the steps: inputting a risk feature matrix generated based on multi-source heterogeneous nursing data into a rule engine and graph neural network model, and outputting a preliminary screening risk event set; taking the primary screening risk event set and the risk feature matrix as input, and constructing a causal conduction map through a causal discovery algorithm; performing risk conduction quantitative integration on each risk event in the primarily screened risk event set based on a causal conduction map to generate a quantitative risk list; based on the dynamic risk priority number and the conduction path chain, reversely tracing to a root cause node along a directed conduction edge, and generating a targeted intervention strategy packet bound with the root cause node; the targeted intervention strategy package is pushed to the nursing responsible person terminal, the strategy execution effect and the risk evolution data are recorded, and a closed-loop disposal database is generated, so that the dynamics and the effectiveness of potential safety hazard analysis of clinical nursing of the neurology department are improved.

The invention discloses a neurology patient rehabilitation nursing method based on multi-modal data analysis, and relates to the technical field of medical health, and the method comprises the steps: extracting neural function features through a multi-modal data fusion algorithm, and carrying out the calculation through a weighted fusion and statistical analysis method, and obtaining a neuroplasticity index vector; combining the neuroplasticity index vector with the unified multi-modal feature representation, carrying out multi-modal abnormal mode recognition analysis, obtaining a rehabilitation risk early warning signal and a personalized intervention suggestion, and generating a personalized rehabilitation scheme; performing dynamic optimization and self-adaptive adjustment on the individualized rehabilitation scheme by using a feedback loop mechanism to generate an optimized individualized rehabilitation scheme; physiological signals in individualized rehabilitation training based on the optimized individualized rehabilitation scheme are collected in real time and preprocessed, and a standardized physiological response data sequence is generated. According to the invention, the scientificity, timeliness and individual adaptability of regulation and control are improved, so that nerve function remodeling is accelerated and the rehabilitation risk is reduced.

The invention relates to an image auxiliary data processing method and system suitable for the neurology department. The method comprises the following steps: acquiring multi-temporal neurology image data and clinical data to generate a standardized spatio-temporal data set; establishing an incidence matrix of lesion areas and symptoms by extracting dynamic features of the standardized spatio-temporal data set; inputting the matrix into a prediction model to obtain a lesion diffusion direction and symptom risk prediction result, visually displaying prediction information through a dynamic indication diagram, and performing closed-loop verification and model optimization in combination with clinical actual data to realize dynamic tracking of a neurological lesion evolution process and intelligent prediction of a symptom development trend. The continuity of illness state analysis and the reliability of a prediction result are remarkably improved, sequential decision support is provided for clinical diagnosis and treatment, and meanwhile the interpretability of a pathological mechanism is enhanced through visual interaction.

The invention discloses a neurology rehabilitation degree evaluation method and system, and relates to the technical field of medical rehabilitation evaluation.The method comprises the following specific steps that data collection is conducted, specifically, whole genome sequencing is conducted on a neurology patient, and whole genome data of the patient is obtained, the method comprises the following steps: collecting initial disease severity degree data of a patient, and evaluating the symptom expression of the patient when the patient sees a doctor for the first time by a professional neurology doctor according to a set disease evaluation standard. A key gene screening strategy and a synaptic plasticity index establishment method are applied to construct a multi-dimensional and more accurate neurology rehabilitation degree evaluation system, so that the neural function repair level is deeply known from the root level of nerve cell connection reconstruction; and accurate prediction and real-time evaluation of the rehabilitation process are realized through the personalized rehabilitation trajectory prediction model, so that the real rehabilitation state of the patient can be reflected more comprehensively and meticulously.

The invention relates to the technical field of medical nursing, in particular to an analysis system based on a data model in the field of neurology nursing. The system comprises a neurology nursing behavior characteristic analysis module, a neurology nursing risk assessment module, a nursing demand and characteristic change rule analysis module and a neurology nursing decision support module. Neurology patient behavior dimension data and neurology nursing record dimension data can be obtained to carry out illness state nursing behavior feature analysis and neurology nursing risk assessment calculation, and a neurology illness state nursing risk assessment value is obtained; the neurology patient nursing demand is obtained, feature change rule mining analysis is carried out, meanwhile, nursing decision support analysis is carried out on the corresponding neurology patient nursing process, a neurology patient nursing decision support suggestion scheme is generated, and corresponding neurology patient nursing decision intervention measures are carried out. The nursing efficiency can be remarkably improved.

The present invention discloses a cerebrospinal fluid sampling and detection device for neurology, and relates to the detection technology field of auxiliary diagnosis of neurological diseases. The present invention comprises a device body, a sampling device is arranged on one side of the device body, a measuring component is arranged on the top of the device body, and a gas injection device is arranged inside the device body. The present invention, through the arrangement of the sampling device, allows the interior of the liquid storage tube to be filled with the required cerebrospinal fluid, and no gaps are left, thereby ensuring that the cerebrospinal fluid in the liquid storage tube is the expected amount, and at the same time, the hollow plug rod, the liquid storage tube, the connecting tube, and the device body cooperate, so that the hollow plug rod fits the inner wall of the liquid storage tube, and the hollow plug rod will inject all the cerebrospinal fluid into the device body, thereby avoiding the residue of cerebrospinal fluid, resulting in the actual amount of cerebrospinal fluid injected into the device body being lower than expected, resulting in insufficient concentration of the final sample, affecting the problem of test results.

The invention discloses a neurology patient body index monitoring system, and particularly relates to the technical field of body monitoring. The environment interaction and adaptation module is used for monitoring and adjusting the surrounding environment of a patient to optimize the health state of the nervous system; the emotion and psychological state monitoring module is used for evaluating the emotion and psychological state of the patient in real time by utilizing an advanced sensing technology and data analysis; and the cognitive function and learning support module is used for monitoring and promoting the cognitive function of the patient to improve neuroplasticity and cognitive ability through interaction and training. By integrating the environment interaction and adaptation module, the emotion and psychological state monitoring module, the cognitive function and learning support module and the comprehensive health ecosystem module, intelligent adjustment of the surrounding environment of a patient, real-time monitoring of the emotion and psychological state, improvement of the cognitive function and comprehensive integration of health resources are achieved; the system optimizes the environmental comfort through intelligent illumination, noise monitoring and air quality adjustment.

The utility model belongs to the technical field of medical instruments, and particularly relates to a neurology severe illness restraining device which comprises a base, a mounting frame and a hanging frame. Universal wheels are arranged at the four corners of the bottom of the base, stand columns are arranged at the four corners of the top of the base, and a bed body is arranged at the tops of the stand columns; the mounting frames are arranged on the two sides of the bed body, a sliding rod is arranged between the mounting frames, a sliding block is arranged on the sliding rod, a fixing screw is arranged on one side of the sliding block, a supporting plate is arranged at the top of the sliding block, a fixing bandage is arranged at the top of the supporting plate, and a lock sleeve and a lock pin are arranged at one end of the fixing bandage; the hanging bracket is arranged at the bottom of the bed body, an inflation pump is arranged on the hanging bracket, and an inflation air bag is arranged on one side of the fixing bandage; the fixing device is reasonable in structure, convenient to adjust the fixing position in the using process, high in flexibility, wide in application range and high in practicability, and meanwhile the comfort of a patient can be improved.

The invention relates to the technical field of intelligent medical multi-modal data analysis and nursing aid decision making, in particular to a neurology nursing risk dynamic early warning and intelligent decision support system. Comprising the steps that a data acquisition module acquires a physiological time sequence and nursing logs to obtain a multi-modal original data set; the feature extraction module performs nonlinear dynamic analysis on the physiological data to generate a state manifold vector, and performs semantic embedding on a log to generate an intervention state tensor containing spatio-temporal features; the causal reasoning module constructs a dynamic causal map, maps vectors and tensors as nodes, and adjusts transmission weights by using the tensors to suppress non-pathological fluctuations; the decision-making module calculates dynamic risks and difference values based on atlas anti-fact deduction, and generates graded early warning and an optimal nursing path; the feedback module updates the atlas parameters according to the processing result. According to the system, the problem of high-frequency false alarm caused by daily nursing actions of traditional monitoring equipment is effectively solved, the alarm fatigue of medical staff is relieved, and focusing on real critical events is ensured.

The invention provides a neurology disease analysis method and system based on deep learning and a medium. The method comprises the following steps: obtaining clinical examination data and image examination image information, processing to obtain a lesion magnitude evaluation index, obtaining self-described symptom information, extracting illness state high-correlation parameter data in combination with the clinical examination data, processing to obtain an illness state evaluation index, and processing to obtain an illness state development evaluation index in combination with the lesion magnitude evaluation index. Operation data of each detection device and medical ability evaluation data of doctors are obtained and processed to obtain detection accuracy influence factors, family medical history data, gene detection data and personal data are obtained and processed to obtain disease development correlation factors; according to the disease development evaluation index, the detection accuracy influence factor and the disease development correlation factor, processing is carried out to obtain a disease risk evaluation index, and the disease prediction level is determined through threshold comparison, so that the timeliness and accuracy of disease prediction are improved based on deep learning according to the examination data and multiple influence factors.

The invention relates to the technical field of neurology department electromyography room nursing, in particular to a patient postoperative rehabilitation guidance system based on neuroelectrophysiology monitoring, which is established on the basis of collecting and analyzing data on the basis of implementing neuroelectrophysiology monitoring on a patient. And a strategy policy of a rehabilitation guidance model is reasonably provided for monitored real-time data. According to the system, on the premise that neuroelectricity monitoring is carried out on a patient to obtain electromyogram data, the electromyogram data are analyzed and screened, and therefore it is guaranteed that a doctor can put forward scientific and effective targeted rehabilitation guidance policies according to comprehensive analysis of all the data; and after an expert makes a rehabilitation guidance policy for the electromyogram data of the patient in a targeted manner according to the system, the rehabilitation guidance policy is stored for a long time through a storage system in the system, so that the working efficiency of nursing is improved.

The invention discloses an off-bed monitoring alarm method and system based on infrared rays and computing equipment. The method comprises the steps that at least one infrared camera is installed above each sickbed in a neurology ward; extracting a bed fixed edge contour in infrared thermal imaging according to a Hough transform algorithm; separating a difference area between a patient and a background from infrared thermal imaging, and performing edge detection on the difference area to obtain a preliminary contour of the patient as an initial position of a Snake model; internal energy and external energy of an energy function in the Snake model are minimized; when the shape of the Snake model does not change any more or reaches a preset number of iterations, taking a convergent model contour as a patient dynamic contour; calculating the relative position of the center of the patient dynamic contour relative to the bed fixed edge contour; when the relative position moves out of the boundary of the preset bed area, alarm information is sent to a central system. According to the method, the contour of the patient is iteratively calculated through the Snake model, and the safety and efficiency of night monitoring of the patient are further improved.

The invention relates to the technical field of medical instrument cleaning, and discloses a neurology nursing instrument rapid cleaning and drying device which comprises a cleaning box, a box door is arranged on the front side of the cleaning box, a liquid containing box is fixedly connected to the inner side of the cleaning box, and a liquid discharging pipe is fixedly connected to the right side of the liquid containing box. A placing unit is arranged on the inner side of the cleaning box, two top blocks are fixedly connected to the inner side of the cleaning box and located above the placing unit, a second fixing pipe is fixedly connected between the two top blocks, a plurality of nozzles are fixedly connected to the lower side of the second fixing pipe, and heat dissipation holes are formed in the upper side of the cleaning box. According to the rapid cleaning and drying device for the neurology nursing instruments, through the arrangement of the cleaning box, the liquid containing box, the spray head, the rotating rod, the rotating disc, the multiple branch plates and the containing box, rotation of the instruments in the containing plate is conveniently controlled, cleaning agents sprayed out of the spray head and cleaning agents in the liquid containing box are used for conducting multi-aspect cleaning on the instruments, and the cleaning effect is improved.

The invention discloses a cerebrospinal fluid sampling and detecting device for the neurology department, and relates to the technical field of detection of auxiliary diagnosis of neurology department diseases. The device comprises a device body, a sampling device is arranged on one side of the device body, a measuring assembly is arranged at the top of the device body, and a gas injection device is arranged in the device body. Through the arrangement of the sampling device, the liquid storage pipe is filled with required cerebrospinal fluid, no gap is reserved, it is ensured that the cerebrospinal fluid in the liquid storage pipe is the expected amount, meanwhile, the hollow plug rod, the liquid storage pipe, the connecting pipe and the device body are matched, and the hollow plug rod is attached to the inner wall of the liquid storage pipe; the hollow plug rod can completely inject the cerebrospinal fluid into the device main body, so that the problems that the amount of the cerebrospinal fluid actually injected into the device main body is lower than the expectation due to the residual cerebrospinal fluid, the concentration of a final sample is insufficient, and the detection result is influenced are solved.

The invention discloses a neurology department clinical nursing potential safety hazard analysis method and device, and relates to the technical field of clinical nursing potential safety hazard analys.The method comprises the steps that physiological data and behavior data of a patient are collected, and multi-source data are preprocessed through weighted Kalman filtering; performing multi-dimensional fusion on the processed data, calculating a comprehensive health score by adopting a weighted average method, and evaluating the potential safety hazard of the patient in combination with a convolutional neural network; and based on the comprehensive health score, generating a personalized nursing scheme, and providing nursing decision support for medical staff. According to the clinical nursing potential safety hazard analysis method for the neurology department, the physiological data and the behavior data are combined, multi-dimensional data fusion is carried out through weighted Kalman filtering and the convolutional neural network, the accuracy of patient health assessment is improved, noise and errors are reduced, and the consistency and reliability of the data are ensured.

The utility model relates to the field of medical auxiliary devices, in particular to a cognitive function rehabilitation training device for the neurology department, which comprises a mounting cabinet, one hundred groups of pressing assemblies, a display screen, an expression lamp assembly, a visual detection sensor, a microphone, a card box assembly and an electric control unit, the pressing assembly is provided with number buttons and an indicating lamp, and each number button is marked with a number selected from 0 to 99; the expression lamp assembly comprises a pleasant expression lamp and a depression expression lamp; the card box assembly is provided with a card temporary storage box and a plurality of card storage boxes; the visual detection sensor can collect digital information on the extracted digital cards. According to the utility model, the cognitive function of a patient is trained by pressing with fingers for many times, judging with the brain, speaking with the mouth and the like, and the interestingness is enhanced by feeding back whether the expression of the expression lamp assembly is accepted or not, so that the patient is pleasant to accept training to promote the rehabilitation of cognitive impairment in multiple aspects of the patient.

The invention relates to the technical field of medical data processing, in particular to a multifunctional neurology intelligent diagnosis system based on 5G and Internet of Things. The system comprises a remote neurology data transmission module used for obtaining neurology data through a 5G vehicle-mounted and indoor base station; the edge data processing module is used for performing edge fusion on the neurology data to obtain neurology fusion data, and performing feature extraction on the neurology fusion data by using a preset edge feature extraction model to obtain neurology feature data; the intelligent diagnosis reasoning module is used for performing feature reasoning on the neurology feature data by using a preset deep feature analysis model to obtain feature reasoning data; and the terminal network regulation and display module is used for carrying out broadband distribution on the feature reasoning data so as to carry out data transmission operation and data visualization operation. According to the method, efficient collaboration between the edge and the cloud can be realized, and an interpretable auxiliary service is provided.

The invention belongs to the technical field of lower limb nursing massage equipment, and discloses a neurology lower limb nursing massage device which comprises a seat body, a mounting plate is connected to the front end of the seat body, a driving lead screw is rotatably connected to the middle of the mounting plate, and a motor is arranged on the mounting plate; the driving screw rod is slidably connected with a first screw seat, the first screw seat is connected with a mounting shaft, and the mounting shaft is rotatably connected with a roller; the driving screw rod is coaxially connected with a driving straight gear, the mounting plate is rotatably connected with two driven straight gears, and the driven straight gears are coaxially connected with a driving belt wheel; the mounting plate is connected with a foot massage box, a driven belt wheel is rotationally connected in the foot massage box, the driven belt wheel is connected with the driving belt wheel through a transmission belt, and the driven belt wheel is connected with a massage ball; the foot massage box and the roller are simultaneously driven by the driving piece to massage the foot sole and the shank of a patient, the massage function is complete, the labor cost is reduced, and rolling type massage can promote blood circulation and improve the massage effect.

The invention is suitable for the technical field of neurology nursing devices, and provides a lower limb position placing device for neurology nursing and a using method thereof, the lower limb position placing device comprises a base, a bearing seat, a fixing plate, a supporting mechanism and a limb bearing mechanism; and the bearing seat is arranged above the base. According to the scheme, the two ends of the bearing seat can be supported at different heights by adjusting the supporting mechanism, the overall supporting angle of the bearing seat and the limb bearing mechanism is adjusted, the lower limbs of a patient can be placed at good limb positions, a self-gravity clamping and limiting structure is formed through the limb bearing mechanism, and when the lower limbs of the patient are placed, the lower limbs of the patient can be clamped and limited by the self-gravity clamping and limiting structure. The guide rod can be driven to slide through the gravity of the lower limbs, then the driven rod is driven to be linked through the transverse plate, the limb supporting plate is synchronously linked through the driven rod and abuts against the lower limbs of the patient, the effect of clamping and limiting the lower limbs of the patient is achieved, the situation that the lower limbs of the patient need to be bound and fixed through a binding belt is avoided, operation is easy, and the labor intensity is greatly reduced.

This application relates to the technical field of electroencephalogram examination, and provides a fixed headgear for neurology electroencephalogram examination and a method thereof. The fixed headgear for neurology electroencephalogram examination includes: a wearing part, which is provided with a plurality of moving grooves and a plurality of positioning holes, and each positioning hole corresponds to at least one moving groove; a plurality of fixing parts, which are movably arranged on the wearing part. The fixing part includes an installation mechanism, a rotating mechanism and a fixing mechanism. The installation mechanism is movably arranged on the wearing part along the moving groove, the rotating mechanism is rotatably arranged on the installation mechanism, and the fixing mechanism is arranged on the rotating mechanism. The fixed headgear for neurology electroencephalogram examination and the method thereof provided by this application can solve the technical problem in the related art that it is time-consuming and laborious to manually adjust the electrode position multiple times by people to a position where good-quality brain wave data signals can be obtained.

The invention belongs to the technical field of surgical instruments, and particularly relates to a multifunctional neurology patient rehabilitation device. The invention provides a multifunctional neurology patient rehabilitation device. The multifunctional neurology patient rehabilitation device comprises an exercise bed and an upper limb exercise mechanism. A lower limb exercise mechanism; and a hand exercise mechanism. According to the multifunctional rehabilitation device for the neurology patient, the upper limb exercise mechanism can assist the patient in arm joint rotation, the lower limb exercise mechanism can assist the patient in leg joint movement, the multi-directional operation effect is achieved through the multi-dimensional rotation function, the movable dimension of the joints of the patient is wider, and the rehabilitation effect of the patient is improved. The hand exercise mechanism is arranged, the patient can be assisted in moving all joints of the fingers, the continuous sectional type movement effect is achieved, manual work is completely replaced through the scheme, the cost can be saved, the effect of simultaneous, accurate and continuous movement of the multiple joints can be achieved, and then the rehabilitation speed of the patient is increased.

The invention relates to the technical field of medical detection and monitoring, in particular to a neurology patient sleep disorder monitoring method, which comprises the following steps: S1, collecting and preprocessing body signals of a patient; s2, constructing a cross-modal association graph, and forming a heterogeneous graph structure with a time sequence weight and a modal label; s3, performing graph convolution and sparse attention operation on the cross-modal association graph, and executing node screening and edge weight updating; s4, time domain and frequency domain decomposition is carried out, and alignment is carried out based on time and frequency indexes; s5, performing segmentation and boundary calibration on the feature sequence, dividing sleep stages, and indexing and storing cross-modal fragments; s6, retrieving abnormal stage fragments, constructing abnormal feature sub-graphs and executing structure clustering operation; and S7, mapping the sleep disorder category labels and the cross-modal features to generate associated features and output results. According to the method, the cross-modal heterogeneous graph is constructed and the time-frequency features are fused, so that the recognition precision and the analysis depth of the sleep disorder of the patient in the neurology department are improved.

The invention relates to the technical field of clinical diagnosis, and discloses a neurology clinical diagnosis device which comprises a hammer handle and a main hammer body at one end of the hammer handle and further comprises a moving-out through opening formed in the bottom of the main hammer body and a hammer head replacement part arranged in the main hammer body. And the pain diagnosis component is arranged at the top of the main hammer body. According to the clinical diagnosis device for the neurology department, four sets of rubber hammering heads of different models are arranged on a replacement disc, when diagnosis operation is carried out, a rotating disc can be rotated to rotate the corresponding rubber hammering heads according to diagnosis requirements, so that a doctor can adjust the stimulation intensity according to the specific conditions of a patient, and the diagnosis efficiency is improved. Therefore, the reflex activity of the patient can be evaluated more accurately, a doctor can know the nervous system condition of the patient more comprehensively, and a more reliable basis is provided for diagnosis.

The utility model discloses a novel neurology department clinical post-stroke limb rehabilitation training auxiliary device in the technical field of stroke limb rehabilitation training, which comprises a fixing frame, universal wheels are respectively arranged on the periphery of the bottom of the fixing frame, two supporting frames are arranged on the top of the fixing frame, sliding blocks are sleeved on the outer sides of the supporting frames, and the sliding blocks are connected with the fixing frame. A fixing rod is installed between the two sliding blocks, the two fixing rods are convenient for a patient to hold, the patient is prevented from falling down and being secondarily hurt during walking rehabilitation training, then the sliding blocks are locked and fixed by using locking fasteners, so that the fixing rod is suitable for people with different heights to use, and the practicability is high. The problems that the human body is prone to inclining or falling down, the human body cannot be supported in an auxiliary mode, the height of an auxiliary device is single, the auxiliary height is inconvenient to adjust to adapt to people of different heights, and the stability and practicability of limb rehabilitation training are affected are solved.

The invention relates to the technical field of patient psychological nursing, in particular to a neurology patient psychological nursing analysis system and method based on an intelligent chip, and the method comprises the steps: analyzing the difference degree of the physiological characteristics of an anxiety patient before and after an operation based on preoperative physiological characteristic data and postoperative physiological characteristic data; based on the symptom reaction data and the operation data of the anxiety patient, analyzing the operation complexity of the anxiety patient; according to the physiological feature difference degree analysis result before and after the operation and the operation complexity degree analysis result, the psychological stress risk of the anxiety disorder patient is evaluated; according to the psychological stress risk assessment result, patient psychological nursing early warning is given to medical staff, by accurately quantifying the psychological stress risk, the high-risk patient can be recognized in the early stage, postoperative acute anxiety, delirium and other complications are avoided, and the operation safety and rehabilitation quality are remarkably improved.

The invention provides a neurology patient remote intelligent monitoring and nursing early warning device and method based on the Internet of Things, the device comprises a hardware part and a software part, the hardware part comprises a sensor module, a wireless communication module, an intelligent terminal device and a wearable device; the sensor module comprises a high-precision heart rate sensor, a blood pressure sensor, a blood oxygen saturation sensor, a brain wave sensor and an acceleration sensor and is used for collecting vital signs and behavior data of a patient in real time; the wireless communication module supports wireless communication technologies such as ZigBee, LoRa and 5G, and ensures real-time transmission of data. By arranging a hardware part, a software part, a sensor module, a wireless communication module, an intelligent terminal device and a wearable device, the problems that an existing traditional monitoring mode depends on field observation or regular inspection of medical staff, efficiency is low, and time and labor are wasted are solved. And important information is easily missed due to insufficient resources of medical staff or limitation of the activity range of the patient.

The utility model relates to the field of neurology, in particular to a neurology nursing support. A nursing support for the neurology department comprises a base, a supporting rod, a top plate, a limiting nail, an elastic piece, a limiting plate and the like, the supporting rod is fixedly connected to the base, the top plate is fixedly connected to the top of the supporting rod, the limiting plate is slidably connected to the supporting rod, a circular groove is formed in the supporting rod, the limiting nail is slidably connected into the circular groove, and the elastic piece is arranged in the circular groove. One end of the limiting plate is fixedly connected into the supporting rod, the other end of the limiting plate is fixedly connected to the limiting nail, and a round hole equal to the limiting nail in size is formed in the limiting plate. The infusion tube is arranged through the limiting plate moving up and down, so that the length of the movable infusion tube can be reduced, the movable infusion tube cannot be wound and folded by a patient, the purpose of unwinding the wound tube is achieved, and the infusion is smoothly carried out.

The invention discloses a neurology index prediction system and method. The method comprises the following steps: firstly, collecting case data of a neurology patient; processing the collected case data to form test data; meanwhile, constructing a neurology index prediction model; inputting test data into the neurology index prediction model for training; and finally, inputting the case data which does not participate in training into the trained neurology index prediction model, and generating a patient neurology disease prediction result from the case data which does not participate in training through the neurology index prediction model. The prediction comprehensiveness is improved through multi-modal data fusion, the detection sensitivity of early functional abnormalities is remarkably improved, the prediction model is more accurate and stable through high-dimensional nonlinear correlation mining and model generalization optimization, non-invasive low cost and clinical interpretability can be considered, invasive detection or high-cost image equipment is not needed, and the method is suitable for large-scale popularization and application. The method is suitable for large-scale screening of basic medical institutions.

The application discloses a puncture assisting device for interventional therapy and belongs to the technical field of neurology. The puncture assisting device comprises a hoop, a cap body in rotational cooperation with the hoop, a first locking member for fixing the hoop and the cap body, the cap body is semispherical, a first opening slot is formed in the cap body along the generatrix of the cap body, and a puncture assembly is slidably arranged in the first opening slot along the length direction of the first opening slot. The puncture assembly comprises a puncture needle, a first ball and a second ball fixed to the outer side of the puncture needle, an arc-shaped slot matched with the second ball is formed in the side wall of the first opening slot, the first ball is matched with a ball sleeve, the ball sleeve is fixedly connected with a guide rod, a sliding support is slidably arranged on the cap body, a guide hole matched with the guide rod is formed in the sliding support, and the guide rod and the sliding support are fixed through a second locking member. The device can position the puncture needle before puncture, is stable in positioning and convenient to adjust.