384 results about "Thoracic structure" patented technology

The invention provides a real-time three-dimensional imaging system in a thoracic surgery, and relates to the field of thoracic surgery auxiliary equipment, and the system comprises a multi-modal image collection module which is used for collecting multi-source data of tissues and organs in a thoracic cavity; the data core processor is used for processing and fusing the multi-source data collected by the multi-mode image acquisition module; the three-dimensional reconstruction module is used for generating a dynamically updated submillimeter-level precision three-dimensional model according to the processed and fused multi-source data and marking a dangerous structure and a safety boundary; and the augmented reality navigation module is used for superposing the three-dimensional model on an operation visual field through a holographic head-mounted display, and realizing real-time three-dimensional visual navigation in combination with instrument tracking and a multi-stage early warning mechanism. According to the invention, radiation-free and high-precision real-time three-dimensional visual navigation can be provided, and the precision and safety in the thoracic surgery can be ensured.

The invention belongs to the technical field of medical imaging and digital twinning, and discloses a thoracic cavity whole organ system level lung four-dimensional EIT detection digital motif and a library building method, and the method comprises the following steps: S1) segmenting multiple organs such as double lungs, heart, sternum, rib and thoracic vertebra central axis skeleton, main bronchus and esophagus based on an individual CT image, and building a three-dimensional geometric model integrated with an EIT electrode array; s2) simulating breathing dynamic deformation by using a solid mechanical model; s3) establishing a coupling relationship between deformation and conductivity, and generating dynamic three-dimensional conductivity distribution; s4) solving an electromagnetic field positive problem, and generating a virtual EIT voltage database synchronous with respiration; the invention also covers pathological model integration and data enhancement strategies. According to the method, a high-fidelity, large-scale and diversified EIT virtual data set can be generated, core data support is provided for training and verifying an AI intelligent reconstruction algorithm, and a model foundation is laid for developing a lung function dynamic digital twinning system.

The invention discloses an OFDM radar vital sign signal separation method based on FGO-VMD and multi-feature clustering, and belongs to the technical field of radar communication integration. According to the method, an OFDM signal radar is used for carrying out human body detection, multi-subcarrier phase difference linear regression is used for estimating displacement, thoracic cavity micro-motion signals are extracted, an FGO-VMD joint optimization model is provided, the modal number and penalty factor parameters of a VMD decomposition algorithm are adaptively determined through minimum envelope entropy, and a multi-feature clustering and weighted reconstruction strategy is designed. And in combination with frequency band screening and correlation coefficient weighting, the separation robustness of the respiratory signal and the heartbeat signal is enhanced, and high-precision separation of the vital sign signal is realized. According to the method, non-contact vital sign detection based on OFDM radar signals is achieved, the problems that in a traditional algorithm, parameters of modal numbers and penalty factors need to be manually set, and signal amplitude attenuation and modal aliasing are caused under complex noise are solved, the vital sign monitoring precision is remarkably improved, and high-precision separation of vital sign signals is achieved.

The invention proposes a thoracic surgery intelligent planning system based on multi-modal image fusion, and relates to the technical field of surgery planning, and the system comprises an image processing module which is used for receiving multi-modal medical image data, carrying out the preprocessing and cross-modal registration of the medical image data, and generating fused image data; the three-dimensional reconstruction module is used for segmenting the key anatomical structure in the thoracic cavity based on the fused image data and constructing a three-dimensional model; the operation planning module is used for generating a candidate operation path scheme according to a multi-objective optimization algorithm based on the three-dimensional model; the interaction adjustment module is used for determining a final operation path scheme and updating a risk assessment result in real time; and the report generation module is used for generating a surgical planning report. The method can solve the problems that the existing multi-modal image registration precision is insufficient, the sensitivity of three-dimensional reconstruction to a tiny anatomical structure is low, and the surgical path planning is lack of dynamic risk assessment and real-time interaction adjustment capability, and realizes the generation and optimization of a high-precision and high-safety thoracic surgery planning scheme.

The invention discloses a monitoring method and system and a related device, which are applied to first electronic equipment, the first electronic equipment is provided with a first circuit, and the first circuit comprises a first electrode, a second electrode, a third electrode, a fourth electrode, an excitation current generation unit and a voltage measurement unit; receiving and responding to a first instruction, and determining that the first electrode and the second electrode are in good contact with skin through a first circuit; first information is determined through the first circuit, the first electrode makes contact with a first position of the user skin, the second electrode makes contact with a second position of the user skin, and the first position and the second position are located at the two ends of the thoracic cavity tissue respectively; and outputting first information, wherein the first information comprises one or more of the following items: cardiac output, stroke output, heart rate, ejection fraction and cardiac function judgment result. Therefore, the heart function condition of the user can be monitored in real time, and the user can conveniently monitor anytime and anywhere.

The invention discloses a point cloud-driven thoracic cavity whole organ dynamic reconstruction and respiration monitoring method and system, and the method comprises the steps: constructing a three-dimensional geometric model corresponding to each target structure in a thoracic cavity based on the thoracic medical image data of a target object, and converting the three-dimensional geometric model into static point cloud data; driving the static point cloud data to perform dynamic deformation simulation in a respiratory cycle based on a respiratory movement rule of the target object to obtain dynamic point cloud data synchronized with a respiratory time phase; performing time-space synchronization association on the dynamic point cloud data and the electrical characteristic parameters, and constructing a digital twin thoracic cavity model; deploying a virtual sensing assembly which dynamically deforms along with the thoracic cavity in the digital twin thoracic cavity model, simulating and monitoring the dynamic breathing process of the target object, and generating a virtual physiological signal; and performing signal processing on the virtual physiological signal to obtain a dynamic reconstruction image reflecting respiratory movement. Continuous simulation of the full-breathing movement process is achieved, and the temporal-spatial resolution and diversity of a virtual database are improved.

A non-contact real-time monitoring system of physiological signs based on millimeter-wave radar includes a millimeter-wave radar and multiple modules for processing radar signals. The millimeter-wave radar is configured to continuously transmit electromagnetic wave signals and simultaneously receive echo signals, perform frequency mixing processing on the echo signals to obtain an intermediate frequency signal, and process the intermediate frequency signal to obtain a radar four-dimensional data matrix. Human body physiological signs are monitored by analyzing body thoracic cavity micro-motion information in signals through the modules; a target echo is processed by adopting a constant false alarm rate detection algorithm, and invalid signals are filtered. A self-adaptive range cell selection algorithm based on short-time stability of respiratory signals is adopted to capture radar echoes reflecting physiological movement. Mixed human body physiological sign signals are processed by using a VMD algorithm, and key parameters in VMD are optimized by using a GWO algorithm.

The invention discloses a thoracic surgery patient postoperative remote monitoring method and system based on the Internet of Things, and relates to the technical field of medical rehabilitation monitoring. Feature index extraction is carried out by taking body position pressure and respiration collaborative response as a two-factor dynamic evaluation basis, so that high-sensitivity judgment on a thoracic cavity load state is formed; after the abnormal state is recognized, body position adjustment is carried out, acoustic feedback analysis is linked, secondary evaluation after body position adjustment is achieved, intervention effectiveness of body position adjustment is ensured, personalized adjustment suggestions are automatically generated, the whole process of'perception-recognition-execution 'of remote monitoring is opened, the intelligent level and response real-time performance of postoperative recovery management are improved, and the postoperative recovery management efficiency is improved. According to the overall scheme, health risks caused by position misjudgment, intervention lag and monitoring blind areas in a traditional system are effectively avoided.

The application discloses a thoracic surgery puncture drainage device, relates to the technical field of medical puncture drainage, and comprises a drainage needle, a drainage tube communicated with the drainage needle, and a negative pressure component communicated with the drainage tube. The negative pressure component comprises an inflatable rubber tube and a shell. An adjusting assembly matched with the inflatable rubber tube is installed on the shell, and the adjusting assembly is used for driving the inflatable rubber tube to stretch and deform. The thoracic surgery puncture drainage device can adaptively drain liquid according to the fluctuation frequency and fluctuation degree of the thoracic cavity when draining the thoracic cavity effusion, effectively reduces the damage to the thoracic cavity, can pressurize and dredge when the drainage tube is slightly blocked, can backwash and dredge when the drainage tube is highly blocked, realizes the integration of dredging and drainage, avoids the backwash and dredging air from entering the drainage device to cause drainage infection, has higher safety, and is more convenient to operate.

The invention relates to the technical field of human body intercostal model trajectory construction, and discloses an intercostal trajectory planning method and system based on an AI reinforcement learning robot. The inter-costal trajectory planning method is applied to an AI robot, and specifically comprises the following steps: S101, receiving an inter-costal region three-dimensional anatomical model construction instruction sent by a user terminal, obtaining anatomical image data of a thoracic cavity from CT or MRI scanning of a patient, and segmenting the anatomical image data by using a deep convolutional image segmentation network to obtain an anatomical image target region; the CT anatomical model and the reinforcement learning technology are fully combined, the completely observable Markov decision model is constructed, the robot path planning strategy is trained in the virtual environment, the robot can autonomously adjust the posture and position of the ultrasonic probe, it is ensured that the probe achieves accurate movement in the complex intercostal region, and the accuracy of the ultrasonic probe is improved. Therefore, limitation of rib sound shadow is broken through, and imaging quality of a target area is remarkably improved.

The invention discloses a thoracic surgery postoperative drainage monitoring data processing method and a thoracic surgery postoperative drainage monitoring data processing system. The method comprises the following steps: synchronously acquiring thoracic respiration dynamic characteristics of a patient and fluid dynamic characteristics of a thoracic closed drainage system through a data acquisition module; the central processing server establishes a time sequence mapping relationship between the two, performs feature fusion analysis, and calculates to obtain a thoracic cavity-pipeline coupling efficiency index; performing logic judgment on the postoperative recovery state of the patient on the basis of the index, and identifying a chest-pipeline fluid transmission state including breathing work limitation, drainage channel blockage and pleural cavity air leakage; and dynamically generating a grading equipment response strategy including adjusting training intensity and triggering pipeline maintenance early warning or analgesia intervention according to an identification result. According to the method, accurate recognition and closed-loop management of postoperative complications are achieved by quantitatively evaluating the linkage relation between respiration driving and drainage response.

The invention provides a non-invasive LVEF monitoring method and system based on millimeter wave radar chest displacement signals. The method comprises the steps that S1, millimeter wave radar signals are transmitted; s2, thoracic cavity micro-motion signals are collected; s3, preprocessing the thoracic cavity micro-motion signal; step S4, separating vital signs; s5, extracting heart failure features; step S6, risk assessment; and S7, outputting a result. According to the invention, a set of non-contact and continuous monitoring cardiac function evaluation system is constructed through creative combination of a radar sensing technology and medical diagnosis, and compared with a traditional LVEF detection method (such as echocardiography, cardiac MRI and the like), breakthrough improvement in clinical practicability, data continuity and technical universality is realized.

The invention belongs to the technical field of medicine, and particularly relates to a method and application for evaluating the respiratory muscle movement function of an IPF patient based on dynamic MRI. Performing dynamic MRI processing on the to-be-tested person to obtain a lung dynamic MRI image; manually marking and segmenting an end-expiratory image and an end-inspiratory image on the lung dynamic MRI image along the inner edge of the thoracic cavity outline, and checking and correcting; obtaining evaluation parameters of chest wall movement and evaluation parameters of diaphragm movement and form by using the images; measuring parameters are analyzed, and the pulmonary fibrosis degree and pulmonary vessel and chest wall muscle parameters of the HRCT image are quantified; and comparing and statistically analyzing the parameters of different to-be-tested persons so as to evaluate the respiratory muscle movement function of the IPF patient. The dynamic MRI technology is adopted, and a quantitative basis is provided for evaluating the respiratory muscle dysfunction and severity of the IPF patient.

The invention discloses a thoracic cavity heart sound signal non-contact extraction system and method based on structured light. The system comprises a structured light projection module, an image acquisition module, an image processing and displacement extraction module and a signal processing and trigger point identification module, structured light is projected on the surface of the chest of a human body to form a regular pattern, and a high-speed image acquisition means is utilized to record micro displacement change generated by light spots under cardiac drive. Thoracic cavity vibration information is extracted through an image processing technology, periodic feature points corresponding to a cardiac rhythm are recognized in combination with a time sequence analysis strategy, a thoracic cavity heart sound signal is extracted, rhythm analysis is conducted, and a cardiac trigger point is output to serve as a trigger signal for synchronous control of medical equipment. The technical problems of signal distortion, equipment interference, potential safety hazards, inconvenience in use and the like in a strong electromagnetic environment in a traditional contact mode are solved, and a high-precision synchronous trigger signal is provided for dynamic imaging.

The invention relates to the technical field of human body breathing micro-motion modeling and holographic imaging, and particularly discloses a radar human body breathing micro-motion 4D modeling and high-resolution holographic imaging method, which is characterized by comprising the following steps of: performing irradiation perception on a human chest target by adopting a multiple-input multiple-output plane radar array; a thoracic cavity target is regarded as a'vector signal source ', namely the thoracic cavity target is equivalent to a set of scattering points of which the spatial positions are mutually discrete; in the geometric model, a graphical representation 3D space coordinate system is established by taking the center of a radar array as an original point and a plane where the array is located as an XOZ plane. According to the radar human body breathing micro-motion 4D modeling and high-resolution holographic imaging method, the micro-Doppler principle is combined, and the micro-Doppler information of each scattering point in the fourth dimension, namely the slow time dimension, is obtained based on the phase decomposition and extraction technology, so that 4D precise reduction of the fluctuation process of the thoracic cavity of the human body is realized.

The invention relates to the field of electrocardiogram treatment, and discloses an individualized electrocardiogram operation process relying on iconography examination and an AI large model, which comprises the following steps: S1, chest CT image acquisition: a CT scanner is used for acquiring chest image data of a patient, the CT scanner can generate high-resolution multilayer CT images, and the data format comprises but is not limited to a DICOM format; s2, heart projection position analysis: carrying out image preprocessing, heart segmentation, heart center point calculation and heart edge positioning on the acquired CT image data; and S3, lead position optimization: generating a lead electrode position based on a heart projection position by using an AI large model. According to the method, the actual position and form of the heart of each patient in the thoracic cavity can be accurately determined through CT image acquisition and heart projection position analysis, and the optimized lead position is generated by utilizing the AI large model based on the individualized projection positions, so that the lead electrode can more accurately capture the electrical activity of the heart.

The application discloses a thoracic cavity closed drainage bottle, which comprises a collecting bottle, a water seal bottle and a pressure measuring bottle, a liquid level alarm assembly and a fan assembly are arranged in the collecting bottle, a connecting pipe is arranged at the top end of the collecting bottle, and a dredging assembly is arranged in the connecting pipe; the liquid level alarm assembly is hung in the collecting bottle; the fan assembly is arranged below the bottom end of the connecting pipe which extends into the collecting bottle; the dredging assembly comprises a pressure increasing part, first opening and closing valves, second opening and closing valves, third opening and closing valves and a side pipe; the first opening and closing valves and the second opening and closing valves are arranged at the top end and the bottom end of the connecting pipe; the pressure increasing part is arranged outside the top end of the connecting pipe, and the side pipe is arranged outside the bottom end of the connecting pipe; and the third opening and closing valves are arranged in the side pipe. The application can monitor the amount of thoracic fluid in the collecting bottle, can determine the tendency of active bleeding in time, can give a prewarning when the amount of thoracic fluid in the collecting bottle is about to be full, and can automatically dredge when the pipeline is blocked during the drainage process, so that the tube pulling operation is not needed, and the pain of the patient is reduced.

The invention discloses a four-dimensional EIT respiration monitoring method based on digital twinborn assistance, which comprises the following steps: firstly, constructing an individualized digital twinborn model which comprises an accurate three-dimensional geometric structure and electrical characteristic parameters and covers thoracic cavity whole organ systems including double lungs, a heart, a central axis skeleton, a main bronchus, an esophagus and the like on the basis of a chest medical image CT of a patient; the method comprises the steps that firstly, a stable and standardized theoretical reference voltage is generated on a model through electromagnetic field simulation, then, virtual-real fusion is conducted on the theoretical reference voltage, a clinically-collected voltage signal in real time and a clinically-actually-measured reference voltage sequence, and finally, a four-dimensional conductivity change image is reconstructed based on the fused dynamic voltage difference. According to the method, reference drift is effectively inhibited, individualized anatomical information is fused, and semi-absolute quantitative evaluation of the pulmonary ventilation function is achieved.

The invention relates to the technical field of robot collision test, and provides a human body model for collaborative robot interaction collision test and a control method thereof, and the human body model comprises a head module which comprises a head supporting part and a head model covering the outer layer of the head supporting part, and a three-dimensional force sensor is fixed on the side surface of the head module; the neck module comprises a neck skeleton rotationally connected with the head supporting part, and a six-dimensional force sensor is arranged at the joint; the trunk module comprises a trunk skeleton hinged to the neck skeleton and a thoracic cavity model covering the outer layer of the trunk skeleton, a plurality of three-dimensional force sensors are arranged on the front chest part of the trunk skeleton, and a three-dimensional force sensor and a flexible sensor are arranged on the back part; the big arm skeleton is connected with the trunk skeleton and is provided with a three-dimensional force sensor; the pose adjusting module comprises a horizontal rotating structure and a linear module, and simulates human body steering and gait movement so as to drive the head module, the neck module, the trunk module and the upper limb module to move and collide with the collaborative robot. Omnidirectional capture and analysis of the space collision force are realized.

The invention relates to the technical field of cardiology department medical devices, and discloses a cardiology department thoracic cavity monitoring first-aid device which comprises a shell, the shell is worn on the chest of a patient through a chest bandage, an external chest compression mechanism is arranged on the shell, and the external chest compression mechanism comprises a first air bag arranged at the bottom of the shell; the shell is connected with an electrode plate for monitoring the respiration and the heart rate of a patient; a rotating disc is rotationally arranged on the shell, an inflation assembly is arranged on the rotating disc, a first air vent is formed in the rotating disc, a second air vent and a communicating groove are formed in the shell, and the second air vent communicates with an inner cavity of the first air bag through the communicating groove. According to the thoracic cavity monitoring and first-aid device for the department of cardiology, through a simple wearing device, when breathing and cardiac arrest of a patient are monitored, first-aid measures of cardio-pulmonary resuscitation can be automatically carried out, autonomous circulation and autonomous breathing are promoted, vital signs of the patient are helped to be gradually recovered, and irreversible damage to the brain and the body of the patient is avoided.

The invention discloses a preparation method and system of a mouse craniocerebral thoracico-abdominal combined injury dynamic model based on AI, and belongs to the technical field of biomechanical injury. The method comprises the steps that impact is applied to a mouse skull, and the impact is conducted along an organ synergistic conduction chain so as to induce the craniocerebral thoracico-abdominal combined injury of the mouse; in the impact applying process, multi-modal physiological data are synchronously collected; and inputting the collected multi-modal physiological data into an AI analysis model, analyzing the injury mechanism of the craniocerebral thoracic-abdominal combined injury, and establishing a dynamic model based on an analysis result. According to the technical scheme provided by the invention, high-simulation modeling of multi-organ cascade injury is realized by constructing the organ synergistic conduction chain from the brain to the thoracic cavity; in combination with multi-modal physiological data synchronous acquisition and an AI analysis model, injury time sequence characteristics can be accurately extracted, a causal path of a local injury initiation system response is established, and the precision and practicability of compound injury mechanism prediction are improved.

The invention relates to the technical field of medical image processing and computer aided design, in particular to a preoperative CT-guided thoracic stent parameterization customization system, which comprises an image processing module for acquiring and preprocessing a patient trachea CT image; the contour segmentation module is used for carrying out trachea contour segmentation on the preprocessed CT image and carrying out correction to obtain trachea three-dimensional contour data; the parameter extraction module is used for extracting morphological parameters of the trachea; the modeling optimization module is used for establishing a stent model according to the morphological parameters of the trachea, constructing a comprehensive objective function which aims at minimizing the geometric matching error of the stent and meeting the mechanical property of the stent, and optimizing the stent model based on the objective function to obtain an optimal stent model; and the parameter output module is used for outputting support design parameters. According to the method, the customization precision and efficiency of the thoracic cavity stent are improved, and the influence of subjective experience factors in a traditional customization method is reduced.

Systems, devices and methods are provided for supporting cardiac function. A device comprises an elongate housing configured for implantation into a patient exterior to the chest cavity. The housing includes a first inlet and an outlet that define a primary blood flow path from the left atrium through at least a portion of the housing within the right atrium, and to the aorta. The housing comprises a motor disposed within the housing and an impeller coupled to the motor for pumping blood from the first inlet to the outlet of the housing through the primary blood flow path. The device bypasses the left ventricle by drawing freshly oxygenated blood from the left atrium and propelling this blood directly into the aorta. Implanting the pump exterior to the chest cavity is less invasive and allows the pump to be quickly and easily repaired, cleaned, repositioned and or replaced without removing or replacing the tubes that are anchored to sensitive tissue structures within the thoracic cavity.

Devices and methods for allowing for improved assisted ventilation of a patient. The methods and devices provide a number of benefits over conventional approaches for assisted ventilation. For example, the methods and devices described herein permit blind insertion of a device that can allow ventilation regardless of whether the device is positioned within a trachea or an esophagus. In addition, the methods and device allow for timed delivery of ventilations based on a condition of a thoracic cavity to increase the amount and efficiency of blood flow during a resuscitation procedure.

The invention discloses a thoracic cavity three-dimensional electrical impedance tomography method and thoracic cavity three-dimensional electrical impedance tomography equipment. The method comprises the following steps: acquiring a three-dimensional point cloud of the appearance of a chest area of a testee to establish a three-dimensional chest model; carrying out equipment self-inspection and checking the bonding condition of the electrode; generating a determined excitation signal and injecting the excitation signal into the testee; acquiring a voltage signal of each electrode; separating EIT and ECG signals and filtering the EIT and ECG signals; according to a three-dimensional thoracic cavity model of the testee, performing positive problem calculation on the voltage signal to obtain the potential of each electrode of the three-dimensional thoracic cavity model; and performing three-dimensional reconstruction by adopting a single-step Gaussian Newton method to obtain a lung ventilation change electrical impedance imaging graph. According to the method, the three-dimensional thoracic cavity model of the testee is constructed, the positive problem solution is performed on the voltage signal, and the image reconstruction is further performed, so that the real-time high-precision three-dimensional dynamic imaging of the thoracic cavity of the testee can be completed, and the imaging accuracy is high.

The utility model belongs to the field of medical instruments, and discloses a puncture bag for chest drainage, which comprises a puncture needle. The guide wire can be arranged in the puncture needle in a penetrating manner; the tip of the guide wire is a J-shaped front end, and the outer wall of the guide wire is provided with a guide wire mark; the expansion tube can be arranged on the guide wire in a sleeving manner; the front portion of the expansion tube is provided with an expansion tube bend, the tail end of the expansion tube is provided with a protruding expansion tube tail end mark, the length from the expansion tube bend to the tail end is larger than the length from the expansion tube bend to the front end, the bending direction of the expansion tube bend is the same as the orientation of the expansion tube tail end mark, and the total length of the expansion tube is equal to the length from the guide wire mark to the J-shaped front end. The drainage tube can be arranged on the guide wire in a sleeving manner. After the guide wire is arranged outside the expansion tube in a penetrating mode, the expansion tube is rotated to the tail end of the expansion tube, the mark faces the lowest position of the thoracic cavity of a patient to indicate the direction of the guide wire, and therefore the opening of the drainage tube is placed in the lowest position of the thoracic cavity, and accurate placement type drainage of pleural effusion is achieved.

The invention discloses an intelligent chest drainage and dynamic monitoring system, which belongs to the field of surgical operations and comprises a drainage tube, a pressure monitoring module, a drainage liquid character monitoring module, a drainage quantity monitoring module, a parameter setting module, a data processing and analyzing module, a display early warning module and a remote communication module. Real-time and accurate monitoring of parameters such as pressure in the thoracic cavity, drainage amount and drainage liquid characters is achieved, postoperative bleeding, air leakage, infection and other complication risks can be found and early warned in time according to monitoring data, the structural design of the drainage tube is optimized, the flexibility and anti-blocking performance of the drainage tube are improved so that the drainage tube can adapt to different operation scenes and patient requirements, and the operation efficiency is improved. A comprehensive and scientific decision basis is provided for clinicians, so that the safety, the effectiveness and the intelligent level of chest drainage treatment are improved.

The invention relates to the technical field of medical equipment, in particular to a multifunctional pleuroperitoneal fluid drainage device and system for treating lung injury, the device comprises a drainage tube, the drainage tube is communicated with a plurality of negative pressure tubes, and the ends, away from the drainage tube, of the negative pressure tubes are communicated with a negative pressure machine used for generating negative pressure suction force; the drainage tube is communicated with a plurality of flushing tubes used for conveying flushing fluid, the outer wall of the drainage tube is further provided with a wriggling mechanism used for externally pushing the drainage tube, the wriggling mechanism comprises a fixed groove body and a pushing wheel, the drainage tube is located in the fixed groove body, and the pushing wheel abuts against the drainage tube; an opening and closing mechanism is arranged on the side, close to the drainage tube, of the fixed groove body and used for communicating the flushing tube with the drainage tube based on pressing of the pushing wheel; the drainage tube is used for reducing the risk of blockage of the drainage tube and maintaining the stability of suction pressure so as to keep continuous extraction of hydrops in the thoracic cavity of a patient.

The invention provides a dynamic liver puncture training model under respiratory movement. The dynamic liver puncture training model comprises a liver puncture training model and a respiratory movement training model, the liver puncture training model comprises a simulated thoracic cavity structure, a simulated organ, a liver movement device and a bottom plate, the simulated thoracic cavity structure is arranged on the bottom plate, the simulated organ is arranged on the simulated thoracic cavity structure, and the liver movement device is arranged at one end of the simulated thoracic cavity structure, is connected with the simulated organ and is fixed on the bottom plate; the respiratory movement simulation device comprises a respiratory movement mechanism and is connected with the liver puncture training model; the respiratory movement mechanism comprises a motor, and the motor converts rotary movement into reciprocating pneumatic displacement conforming to physiological laws on the basis of a human respiratory movement mathematical model. Through the liver puncture training model and the breathing movement simulation device, the motor is constrained through a human body breathing movement mathematical model, the influence of liver movement on puncture operation in the breathing process is precisely reduced, and a key technical guarantee is provided for simulating a real operation environment.

The invention relates to a method for preventing and monitoring blood pressure based on terahertz radar electrocardiogram heart rate variation parameters, and belongs to the field of terahertz radar signal processing. The method comprises the steps that a human thoracic cavity micro-motion signal is collected through a terahertz radar, an intermediate frequency signal is obtained through ADC sampling, distance dimension Fourier transform and phase unwrapping processing are carried out, and a target object is obtained; extracting a chest displacement signal containing heartbeat information; band-pass filtering is adopted to preliminarily separate respiration and heartbeat signals, and variation mode decomposition optimized by an ant colony algorithm is introduced to effectively suppress respiration harmonic interference; inputting the heartbeat signal into a multi-modal deep learning framework fusing a convolutional neural network, a long-short-term memory network and a multi-head attention mechanism to realize end-to-end high-precision reconstruction from a radar mechanical vibration signal to a standard electrocardio waveform; r peak detection is conducted on the reconstructed radar ECG signals, and time domain and frequency domain heart rate variability parameters are calculated and used for evaluating the autonomic nerve function state. The method has the effect of improving the monitoring comfort of special crowds.