900 results about "Av conduction" patented technology

The invention provides an artificial intelligence auxiliary diagnosis method and system for a knee joint, and the method comprises the steps: synchronously collecting a multi-angle dynamic X-ray image and six-degree-of-freedom contact force distribution data in an articular cavity, dynamically tracking a patella sliding track, and generating a mechanical phase track; a personalized knee joint model is constructed in combination with the biological parameters of the lower limbs of the patient, the mechanical phase trajectory and the contact force data vector are superposed to generate a dynamic mechanical fingerprint, and then the dynamic mechanical fingerprint is mapped into a biomechanical attribute map; electromyographic signal time-frequency characteristics and tibia rotation angles in the movement process are collected, an electromyographic activation mode is constructed, and the electromyographic activation mode and a biomechanical attribute map are subjected to characteristic fusion to form a joint dynamics comprehensive contour; analyzing a stress wave conduction path by using a joint anomaly dynamic propagation model to identify a compensatory injury mode; a diagnosis map is generated according to the recognition result, a preset biomechanical constraint condition is matched to correct the diagnosis map, and an individualized rehabilitation strategy is formulated. The treatment effect is improved, and the recovery speed of a patient is increased.

The invention discloses an anesthesia equipment fault diagnosis method and system based on image recognition, particularly relates to the technical field of medical equipment fault detection, and is used for solving the problem that a non-contact image detection method in existing anesthesia equipment pipeline leakage detection is poor in transparent pipeline weak leakage signal recognition capability. Through combination of multispectral dynamic imaging and polarized light scattering mode analysis, pipeline surface microscopic deformation characteristics are obtained, and a leakage path prediction result is generated. Environmental reflective noise is inhibited based on spectral distribution characteristics of the reference image set, optical response changes of the candidate area are triggered in combination with active pressure disturbance, and the inverse proportion physical relation between the permeation rate and the fluid conduction speed is verified; through dynamic threshold screening and spatial continuity verification, accurate positioning of a target area is realized, finally, spectral features, path forms and real-time pressure parameters are fused to generate leakage risk assessment, non-intrusive high-sensitivity leakage identification is realized, and reliable guarantee is provided for safe operation of clinical anesthesia equipment.

The invention relates to the technical field of medical care informatics, and discloses an intelligent post-stroke cognitive impairment assessment method based on brain network dynamic reconstruction, which comprises the following steps: acquiring multi-modal brain image data of a patient, dynamically compensating the difference between haemodynamic delay and white matter conduction velocity through a nerve-blood vessel coupling model, and calculating the post-stroke cognitive impairment; precise space-time alignment of function and structure signals is realized; a pulse neural network dynamic entropy change model is constructed based on the alignment data, functional connection strength change is coded into a pulse distribution sequence, and Gamma wave band synchronization enhancement and other compensatory features are extracted; constraining rationality of brain network reconstruction by adopting an energy optimal transmission model, and generating a compensatory thermodynamic diagram; and real-time calculation of the edge end is realized through pulse time sequence compression coding. The limitation of traditional static analysis is avoided, the algorithm achieves microsecond response on embedded equipment through the pulse coding technology, and a reliable stroke rehabilitation evaluation tool is provided for primary hospitals.

The invention discloses an insertion tube and a manufacturing method thereof, an insertion part and an endoscope, and relates to the technical field of medical instruments, the insertion tube comprises an insertion body and an elastic tube, a first reinforcing layer and a second reinforcing layer are arranged in the insertion body, the second reinforcing layer is arranged outside the first reinforcing layer in a surrounding mode, and the first reinforcing layer is provided with a concave part. The first reinforcing layer and the second reinforcing layer can form double limiting and wrapping supporting on the elastic pipe, the concave shape of the concave part of the first reinforcing layer is utilized to be attached to the outer wall outline of the elastic pipe, and the outer side of the second reinforcing layer is matched for enclosing and restraining, so that the installation stability of the elastic pipe in the first channel can be greatly improved; bending moment generated by self-gravity, external force and the like of the elastic tube is effectively counteracted, the elastic tube is prevented from being bent under the action of self-gravity, external force and the like, the whole insertion tube is prevented from deforming along with bending of the elastic tube, and the form stability of the insertion tube in the cavity in the propelling process is guaranteed. And the straightness of a traction rope transmission path and the accurate conduction of a control instruction are ensured.

The invention discloses a heart failure combined left beam branch conduction block classification method based on feature fusion, and the method comprises the steps: extracting radiomics features and deep learning features through a heart magnetic resonance image, carrying out the feature fusion and selection, constructing a classification model through a machine learning algorithm, and carrying out the classification of the heart failure combined left beam branch conduction block. According to the method, the advantages of deep learning in the aspect of image processing and the high efficiency of machine learning in a classification task are combined, and complex information of a heart image can be reflected more comprehensively and accurately by combining radiomics features and deep learning features; an automatic and intelligent feature extraction and classification method is utilized, a large amount of medical image data can be rapidly processed and analyzed, accurate classification of the heart failure combined left bundle branch conduction block is achieved, the method has higher classification accuracy and higher robustness, and in the field of medical image classification, the method has the advantages that the classification accuracy is improved, and the classification efficiency is improved. And the efficiency and the quality of medical services can be improved.

The invention relates to the technical field of medical health data information decoding analysis and processing, and particularly discloses a dynamic pain nerve decoding and intervention system based on a prefrontal lobe time sequence characteristic window, which comprises a signal acquisition module, a dynamic window control module, a phase prediction module, an intervention execution module and an event driving controller. The dynamic window control module intelligently adjusts the duration of a signal analysis window through real-time calculation of the energy ratio of a # imgabs 0 # frequency band to a # imgabs 1 # frequency band, and accurately locks a transient characteristic window in a pain outbreak period; the phase prediction module realizes millisecond-level synchronization of stimulation pulse and a rising edge of action potential of a neural cluster based on a two-factor mapping mechanism of an individualized conduction velocity level and an oscillation frequency; the event-driven controller reduces the power consumption to a wearable device level while maintaining 10 ms-level real-time response through a dynamic resource allocation strategy.

The invention discloses an adjustable auxiliary device for ultrasonic diagnosis in the obstetrics and gynecology department, relates to the technical field of medical treatment, and aims to solve the technical problems that a coupling agent is easily contracted and extruded by muscles, so that detection is inaccurate, and misdiagnosis is easily caused. According to the invention, the extrusion sheet which deforms due to the influence of human body temperature is utilized to automatically supplement the coupling agent, ensure the coherence of the detection process, shorten the time and reduce the discomfort of the patient and the influence risk of the detection result. The elastic clamping sheet is matched with the elastic clamping groove to dynamically adjust the supplement amount of the coupling agent, so that sufficient coupling agent at each detection part is ensured, ultrasonic conduction is stable, and accurate diagnosis is assisted. The spiral guide body design of the coupling agent guiding mechanism can guide the redundant coupling agent to flow and prevent the redundant coupling agent from dripping at the bending position, and the probe circuit can be protected. The grab handle and the pressure suction mechanism work cooperatively to efficiently collect redundant coupling agents, so that the cleaning workload is reduced, and the detection convenience is improved.

The invention discloses a motor cortex excitability evaluation method based on threshold tracking magnetic stimulation, and relates to the technical field of biomedical engineering. The motor cortex excitability assessment method based on threshold tracking magnetic stimulation comprises the following steps: performing electrical stimulation on median nerves of a wrist of a subject, recording on an abductor politics brevis (APB), recording a stimuli-response curve, determining a stimuli-response (SR) curve of cortex stimulation by increasing the magnetic stimulation intensity to the following level, and determining the stimuli-response (SR) curve of cortex stimulation according to the stimuli-response (SR) curve. And calculating statistical parameters of the average value and the standard deviation of the excitability threshold values, and judging the dynamic trend of cortical excitability. According to the method, the stimulation-reaction curve of cortex stimulation is determined by improving the magnetic stimulation intensity to the following level, the central movement conduction time is calculated through the F-wave method based on the stimulation-reaction curve, initial stimulation and threshold determination are completed, subsequent threshold tracking is carried out on the technology, and the accuracy and the reliability of the system are improved. And an efficient and accurate brain motor cortex function detection means is provided for diagnosis of nervous system diseases.

The utility model relates to the technical field of medical instruments, and discloses an energy surgery active cooling device and an energy surgery active cooling system. The second clamping body is connected with the first clamping body, and the far end of the second clamping body is suitable for abutting against the far end of the first clamping body; the cooling structure is arranged on at least one of the first clamping body and the second clamping body; the interior of the cooling structure is hollow and forms a containing cavity, and the containing cavity is suitable for containing a cooling medium; the containing cavity communicates with an external cold source, and the containing cavity is suitable for circulating a cooling medium between the containing cavity and the external cold source so that heat on the first clamping body and / or the second clamping body can be conducted to the external cold source from the far-end tip end. According to the active cooling device for the energy surgery department, the heat risk of the heating surface is eliminated, the heat dissipation and cooling efficiency of the clamping body is improved, the heat dissipation structure of the clamping body is simplified, and the process difficulty of the device is reduced.

The invention relates to the technical field of intelligent medical auxiliary diagnosis and neural function automatic evaluation, in particular to an NIHSS score automatic evaluation system for a stroke patient. Comprising a multi-mode induction and perception unit which is used as a front-end data entry and is used for collecting patient response in real time to generate a video stream containing depth and color information and a synchronous audio stream; the dynamic reference calibration unit is used for extracting kinematic characteristics to construct an individualized nerve reference template; the neural motion spectrum decomposition unit is used for generating a spectrum pathological feature vector for distinguishing myasthenia and ataxia; the opposite-side image rejection analysis unit is used for generating compensation and driving confidence for representing a real nerve driving intention; the cross-modal reflection analysis unit is used for generating a sensory pathway integrity index according to the nerve conduction velocity difference; and the collaborative scoring decision engine is used for mapping the multi-modal features into standardized NIHSS scores. According to the method, the interference of age and basic physique on scoring is effectively eliminated, and a high-precision comparison reference can be provided for subsequent abnormal judgment of the affected side.

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.

The invention relates to a nerve monitoring monopole electrocoagulation hook for thyroid surgery and a surgical instrument, and relates to the technical field of medical instruments.The electrocoagulation hook comprises a nerve detecting piece installed at the front end of a handle, an insulating pipe body is arranged in the nerve detecting piece, a smoke suction channel and a sliding hole are formed in the insulating pipe body, and a rod body is slidably inserted into the sliding hole and connected with an external power source; the far end of the rod body is provided with a hook body bent relative to the rod body, and the surface, deviating from the smoke suction channel, of the hook body forms an electrocoagulation face. The hook body is provided with a first-stage heat conduction assembly, avoids the electrocoagulation surface and is in heat conduction connection with the electrocoagulation surface; one end of the second-stage heat conduction assembly is in heat conduction connection with the first-stage heat conduction assembly, and the other end of the second-stage heat conduction assembly extends into the smoke suction channel. Through the combined design of two-stage heat conduction and heat dissipation, heat generated by the electrocoagulation surface during coagulation and cutting can be rapidly conducted through the heat conduction assembly and is dissipated and taken away through cooperation of the smoke suction channel, so that the diffusion risk of the heat in adjacent nerves and tissues is reduced to a certain extent, and the operation safety and stability in an operation are improved.

The invention relates to the technical field of medical big data analysis, and discloses a hospital medical record data anomaly analysis method based on big data. According to the method, multi-source medical record data including diagnosis and treatment event records, nursing operation sequences and patient sign monitoring streams in a hospital information system are collected, and structured reforming is carried out. And constructing a medical record element interaction graph based on the reformed data, and detecting an abnormal state conduction path between the data elements through the graph model. And performing hierarchical traceability calculation according to the detected conduction path, positioning an abnormal source and generating a positioning report, and finally outputting a calibration instruction set according to the report. According to the method, the abnormal conduction chain is systematically identified from the correlation perspective, and the root source of the abnormality can be automatically and accurately traced, so that the logicality and the positioning accuracy of the medical record data abnormality analysis are improved.

The invention relates to a nursing shift information association method and system based on a dynamic knowledge graph, and belongs to the field of data processing. The method comprises the steps of integrating multi-dimensional data of a patient and outputting a situation matrix, the multi-dimensional data of the patient comprises a basic portrait of the patient, a dynamic index, a treatment process and a nursing focus, and the situation matrix comprises acute degree, vulnerability and intervention priority; acquiring and analyzing a nursing shift information text, and outputting a clinical event set with a corrected potential energy value based on the situation matrix and the nursing shift information text; carrying out direct effect projection and risk conduction modeling based on the clinical event set, and outputting an aging curve and a risk event set carrying a risk value; and constructing a dynamic knowledge graph based on the clinical event set, the timeliness curve and the risk event set. According to the invention, multi-source clinical data are integrated through the dynamic knowledge graph, and intelligent association of nursing shift information is realized.

The invention discloses a non-invasive wearable vascular arteriosclerosis assessment system and method based on multi-mode pulse wave signal fusion, and belongs to the field of vascular function assessment. The system comprises a distributed acquisition front end, a butterfly-shaped flexible substrate, an integrated double-accelerometer, a four-wavelength LED (530nm / 660nm superficial blood vessel measurement), a 810nm / 940nm deep artery measurement device, a double-photodiode, a double-impedance electrode and a pressure sensor. The central integrated control end processes a multi-mode signal and realizes pressure-LED current closed-loop control; the upper computer terminal extracts the multi-modal pulse wave time difference of the limbs and the neck, the local and regional pulse wave conduction velocity and the blood oxygen hemoglobin change parameters induced by the standardized posture, the dimension is reduced to 30 through principal component analysis, then the parameters are input into the random forest regression model, and the vascular elasticity index is output. Signal stability is improved through flexible fitting, single-source limitation is solved through multi-modal fusion, signal quality is guaranteed through closed-loop control, sensitivity is enhanced through dynamic physiological excitation, and accuracy and universality of arteriosclerosis assessment are improved.

The invention provides a rehabilitation training feedback system and method. The method comprises the following steps: acquiring a surface electromyogram signal; a plurality of activation trend indexes are determined through the surface electromyogram signals, and then muscle force activation points of different muscle areas are extracted from the surface electromyogram signals according to all the activation trend indexes; performing collaborative analysis on the basis of a function collaborative relationship in combination with all muscle force activation points to obtain time sequence response tensors between all motion joints and corresponding muscle areas when motion responses are inconsistent; according to the joint angle information and the time sequence response tensor, constructing a functional coupling graph, and further performing kinematic chain simulation on a rehabilitation training process through the functional coupling graph to obtain a response consistency index; and performing feedback control on the rehabilitation training process of the patient according to the response consistency index in combination with a preset consistency threshold. By means of the scheme, feedback control can be conducted on rehabilitation training of the patient based on the space-time coupling relation between muscle group microstructure changes and mechanical conduction characteristics.

The invention relates to the technical field of temperature sensors, in particular to a temperature sensor dynamic response acceleration method and system for medical liver testing, and the method comprises the steps: collecting an original temperature measurement sequence outputted by a main temperature sensor in a first target region in real time, synchronously acquiring a reference temperature sequence output by a reference temperature sensor located in a second target area; and based on the physical characteristics of the main temperature sensor and the heat exchange characteristics of the liver tissue, constructing a sensor and liver tissue dynamic response model containing key dynamic parameter vectors. The dynamic response model of the sensor and the liver tissue is constructed, the dynamic characteristics of the sensor and the tissue in the current environment can be accurately quantified, thermal inertia and conduction delay are actively compensated from the algorithm level through the model inverse function, the real-time performance of temperature monitoring is remarkably improved, and the temperature monitoring accuracy is improved. And a timely and reliable feedback signal is provided for closed-loop control.

Example approaches are directed to an apparatus for reducing smoke created by a surgical instrument in a procedure, e.g., as part of a surgical system. The apparatus may include an insulating vessel and a flexible printed circuit disposed within the vessel, with the vessel including an inlet and an outlet. The flexible printed circuit includes a substrate layer and a conductive layer disposed on the substrate. The conductive layer includes two charge conducting portions or electrodes having opposite electrical charges, which are spaced apart by an electrically insulated portion. The charge conducting portions are positioned between the inlet and outlet of the vessel such that particles entering the inlet are electrically charged and drawn to one of the charge conducting portions.

According to the three-dimensional electric field coupling modeling method for analgesia provided by the invention, the propagation process of an electric field in each physiological tissue is accurately simulated by constructing a multi-layer bionic tissue model, so that the accuracy and effect of analgesia treatment are improved; calculating the conductivity and dielectric constant of each layer of tissue, performing numerical simulation on electric field distribution by using a finite element analysis technology, optimizing electrode configuration and electrical stimulation parameters, and ensuring the uniformity and stability of the electric field of a target area; a neurophysiology model is integrated, the conduction law of nerve fiber action potential is dynamically simulated, the stimulation effect of electric field intensity on nerve fibers is quantitatively analyzed, analgesia parameters are further optimized, and accurate control over pain signal transmission is achieved. The problems that in an existing electrical stimulation technology, electric field distribution is not uniform, electrode contact is not stable, and the stimulation effect is difficult to last are effectively solved, wide clinical application prospects are achieved, and an efficient, stable and accurate solution is provided especially in non-invasive treatment of chronic pain.

The invention relates to the technical field of medical treatment, in particular to an intra-abdominal pressure adjusting device and method.The device comprises an adjustable support used for supporting a skin contact assembly and allowing the position and angle of an electromagnet to be adjusted; the electromagnetic adsorption assembly is fixed on the adjustable bracket and is used for lifting the abdominal skin of the patient according to an electromagnetic adsorption effect so as to reduce the abdominal wall pressure; the skin contact assembly connected with the electromagnetic adsorption assembly is used for being attached to the skin of a patient and forming a sealed space; the control assembly is electrically connected with the electromagnetic adsorption assembly and used for collecting current pressure data and dynamically adjusting current output of the electromagnetic adsorption assembly according to a preset pressure threshold value and the current pressure data. Therefore, the problem that in the prior art, although the body position therapy can relieve the gravity compression of the abdominal wall, in a critical patient needing to be kept in a semi-reclining or upright position, the reverse effect of chest pressure conduction and diaphragm downward movement possibly aggravates the pressure load of the abdominal cavity is solved.

Apparatus and methods for deactivating bronchial nerves and ablating smooth muscle extending along a bronchial branch of a mammalian subject to treat asthma and related conditions. An ultrasonic transducer (11) is inserted into the bronchus as, for example, by advancing the distal end of a catheter (10) bearing the transducer into the bronchial section to be treated. The ultrasonic transducer emits ultrasound so as to heat tissues throughout a relatively large impact volume (13) to a temperature sufficient to inactivate nerve conduction and ablate smooth muscle but insufficient to cause rapid ablation or necrosis of the surrounding tissues. The treatment can be performed without locating or focusing on individual bronchial nerves or smooth muscle.

The invention relates to an intelligent dynamic negative pressure and phototherapy integrated burn wound treatment device, and belongs to the technical field of medical instruments, the device comprises a contact layer, a conduction layer and a honeycomb support layer, the contact layer drains exudate, the conduction layer is integrated with an optical fiber network and a self-adaptive deformation mechanism, and the honeycomb support layer is connected with an intelligent negative pressure chamber and a gradient sterilization system. The pressure of the negative pressure chamber is dynamically adjusted through a corrugated air bag and a rhombic telescopic unit, and the photo-thermal assembly irradiates the wound surface in a time-sharing mode and maintains the constant temperature. And the sterilization system adopts ultraviolet pulse and a multi-stage filter screen to cooperatively purify the percolate. The intelligent regulation and control module optimizes treatment parameters in real time through a multi-mode sensing network, and full-closed-loop cooperation of negative pressure, phototherapy and sterilization is achieved. According to the device, the limitation of traditional treatment is broken through through integrated design, the wound repairing quality and the anti-infection capacity are remarkably improved, meanwhile, the medical care burden is reduced through modular expansion and a non-invasive monitoring function, and an efficient and safe intelligent solution is provided for burn management.

The invention relates to the technical field of ultrasonic imaging, and provides an ultrasonic pulse wave imaging method, device and equipment, and the method comprises the steps: calling an ultrasonic probe to carry out B-mode scanning, and determining the sampling position of a target blood vessel; aiming at the sampling position, calling the ultrasonic probe to carry out M-mode single-line scanning, determining first diameter dynamic change information of the blood vessel wall of the target blood vessel, and determining a first pulse wave conduction velocity based on the first diameter dynamic change information; aiming at the sampling position, calling the ultrasonic probe to carry out M-mode double-line scanning, determining second diameter dynamic change information of the blood vessel wall of the target blood vessel, and determining a second pulse wave conduction velocity based on the second diameter dynamic change information; and comprehensively displaying the first pulse wave conduction velocity and the second pulse wave conduction velocity. According to the technical scheme provided by one or more embodiments, the local pulse wave conduction velocity of the blood vessel can be effectively obtained.

The invention belongs to the technical field of medical health care equipment, and particularly provides a treatment control method of an intelligent self-adaptive wave conduction health care instrument, which comprises the following steps of: acquiring a physiological state signal of a user in real time, and generating an abnormal trigger instruction when the physiological state signal is detected to deviate from a preset health threshold range; inputting physiological index data corresponding to the abnormal trigger instruction into a dynamic adjustment model, wherein the dynamic adjustment model generates a treatment scheme based on a mapping relation between physiological indexes and wave conduction parameters; generating a driving control signal according to the treatment scheme, wherein the driving control signal is used for adjusting a particle resonance wave output device in the wave conduction health care instrument; and outputting a target particle resonance wave through a particle resonance wave output device according to the resonance frequency and the amplitude corresponding to the driving control signal, and continuously driving the action duration corresponding to the control signal. By collecting the physiological state signal of the user in real time and dynamically comparing the physiological state signal with the preset health threshold value, accurate anomaly detection and immediate intervention are achieved, and the limitation of fixed parameter output of traditional equipment is broken through.

The invention discloses a multifunctional cardiovascular monitoring system which comprises an electrocardiosignal acquisition module, a conduction block feature extraction module, an arrhythmia classification processing module, a cardiac function parameter calculation module, an intelligent diagnosis analysis module and a monitoring data output module. The electrocardiosignal acquisition module acquires and transmits original signals, the conduction block feature extraction module extracts feature parameters by using an exclusive algorithm, the arrhythmia classification processing module obtains classification results through a multi-dimensional classifier, and the cardiac function parameter calculation module generates calibration parameters by using a dynamic calibration model in combination with the classification results. The intelligent diagnosis analysis module generates diagnosis data through comprehensive analysis of the auxiliary platform, and the monitoring data output module processes the data and then outputs the data. The system realizes module cooperation and data interaction, improves the monitoring efficiency, guarantees data accuracy by using a professional algorithm and a model, and provides reliable support for clinical cardiovascular monitoring.

The application provides a heart electrophysiology simulation system, comprising: an image acquisition module for acquiring a plurality of thoracic cavity images; the three-dimensional grid reconstruction module is used for obtaining a ventricle three-dimensional grid through a finite element method according to the plurality of thoracic cavity images; the ventricular conduction network construction module is used for generating a ventricular conduction network according to the ventricular three-dimensional grid, the ventricular conduction network comprises a plurality of first grid points, and the geometric position of each first grid point shares the point cloud of the ventricular three-dimensional grid; the electrophysiological parameter simulation module is used for simulating the conduction process of the heart action potential in the ventricle according to the geometric position of the first grid point and electrophysiological parameters, and the electrophysiological parameters comprise cell level parameters and tissue level parameters; and the dynamic simulation module is used for simulating the cardiac electric signal according to the conduction process of the cardiac action potential in the ventricle to obtain a dynamic simulation result.

The invention provides a balloon endoscopic system for intravascular direct vision examination, and relates to the technical field of medical instruments, the balloon endoscopic system comprises a catheter, a balloon capable of being filled and discharged, an endoscope lens, a light source assembly and an image transmission processing module, a cavity channel used for containing the endoscope lens and a conduction component of the light source assembly is formed in a catheter body of the catheter, and the catheter body of the catheter is internally provided with a cavity channel used for containing the endoscope lens and the conduction component of the light source assembly; the filling pipeline is used for supplying liquid to the inflatable and deflatable balloon; the inflatable and deflatable balloon is fixedly connected to the outer surface of the front end of the catheter, and the inflatable and deflatable balloon is used for bulging after being conveyed to a target position in a blood vessel. The inflatable and deflatable balloon can block blood flow and open the blood vessel wall after bulging and is matched with transparent filling liquid injected into the filling pipeline, residual blood can be further removed, a blood-free observation window is formed, interference of blood on imaging is avoided, and a foundation is laid for clearly observing the condition of the blood vessel wall. The inner wall of the balloon is coated with a nano anti-fog coating, so that the penetrability of a light source is ensured, and the fogging surface influence caused by blood residue or temperature difference can be avoided.

The invention relates to the technical field of medical instruments, and particularly discloses an ankle arthroscope traction device convenient to install, comprising a traction frame used for traction and stretching of an ankle joint; the device further comprises a positioning supporting base. The positioning support base limits the position of the traction frame; the detection mechanism is installed in the positioning supporting base and detects the thickness degree of the middle of the shank of the patient before traction of the ankle joint of the patient; according to the detection mechanism, when the rotary detection roller rotates, the cam rotates synchronously, the eccentric contour of the cam pushes the displacement sensing plate to slide in the sliding rail in the positioning supporting base, and the first reset spring provides reset force. A protruding structure at the bottom of the displacement sensing plate accurately acts on the pressure sensing air bag, the pressure sensing air bag is connected with the elastic reset element through the connecting pipe air guide pipe, displacement is converted into deformation of the elastic reset element, then the displacement transmission rod is driven to move, and transmission of physical signals is completed.

The invention provides a recessive gastroesophageal reflux event data analysis system and method based on dynamic changes of abdominal pressure. The system and method are suitable for noninvasive detection of atypical reflux clinically. The system comprises an abdominal pressure dynamic detection unit, a throat vibration detection unit, a multi-mode signal processing module, a reflux event judgment module and a data output module. According to the system, by analyzing time sequence linkage between abdominal pressure mutation and throat vibration, a stomach content countercurrent event is recognized, silent type countercurrent characteristic sound is captured with the assistance of a bone conduction sound wave channel, and multi-path redundancy recognition is achieved. The method is suitable for postoperative patients, children, old people and other people who cannot complain, has the technical advantages of continuous wearing, behavior correlation analysis and clinical verifiability, and significantly improves the recognition rate and diagnosis accuracy of recessive gastroesophageal reflux events.

The invention discloses a medical critical risk prediction method based on physical sign data monitored by a smart watch, and relates to the technical field of critical monitoring, and the method comprises the steps: constructing a multi-dimensional physical sign fusion analysis model, collecting dynamic physiological parameters in real time through the smart watch, and updating a personalized health baseline; based on the personalized health baseline, detecting a pathological fluctuation mode in the dynamic physiological parameters through a time sequence convolutional network; inputting the identified abnormal waveform features into a risk prediction model optimized by transfer learning, and calculating a coupling risk index of the multi-organ system; establishing a three-level response early warning mechanism based on the coupling risk index of the multi-organ system; and generating an intervention scheme based on the coupling risk index of the multi-organ system. Compared with the prior art, the intelligent wearable device has the advantages that the multi-organ risk conduction model is combined, the severe risk is accurately predicted, a risk identification-early warning-disposal dynamic management system is formed, and the clinical practical value of the intelligent wearable device in a pre-hospital emergency scene is effectively improved.