507 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 belongs to the technical field of medical instruments, and discloses a dynamic pressure adjusting thoracic surgery anti-blocking drainage system which comprises a drainage tube, a drainage bag, a backflow tube, a positioning disc, an electric rotating disc, a blade, an electric vacuum pump and a monitoring mechanism. A drainage tube and a return tube are arranged on the special-shaped tee joint; the tail end of the return pipe is connected with the input end of the electric vacuum pump; the output end of the electric vacuum pump communicates with the drainage bag; a protective shell is arranged on the positioning disc; an electric turntable is arranged on the protective shell, a plurality of blades are arranged at the tail end of a movable rod of the multi-stage medical electric push rod, and a monitoring mechanism is arranged on the protective shell. The internal pressure of the thoracic cavity is monitored in real time, the drainage process is accurately controlled in combination with other physical sign data, and the proper pressure of the thoracic cavity is maintained to improve drainage efficiency; a real-time monitoring and abnormity identification function can timely perceive drainage abnormity; normal saline flushing and mechanical crushing are combined, so that the drainage tube is smooth; the drainage process is comprehensively evaluated in combination with various monitoring data, and potential risks are found as early as possible.

The invention discloses a driver health monitoring and early warning method and system, and belongs to the technical field of automobile intelligent cabins, and the method comprises the steps: calling camera data in a DMS in an intelligent cabin, positioning the chest of a driver, and obtaining three-dimensional coordinates of the chest part of the driver in a driving cabin space; adjusting a millimeter wave radar integrated in a steering wheel to send a radar signal by combining the three-dimensional coordinates positioned to the chest part; receiving an echo signal of the radar signal interfered by the fluctuating cavity motion of the thoracic cavity part; carrying out real-time extraction on a respiration signal and a heartbeat signal based on the echo signal to obtain a vital sign signal; performing feature extraction on the vital sign signals to obtain vital sign parameters; analyzing the vital sign parameters; and when the vital sign parameter exceeds a threshold value, sending an exception handling request. According to the method, cardiopulmonary data of a driver are analyzed, and occurrence of sudden cardiopulmonary diseases such as inhibitory respiration and heartbeat pause is judged in advance.

The invention belongs to the technical field of sleep respiratory disease detection, and relates to a sleep apnea identification method based on a hybrid neural network, which comprises the following steps of: sensing human sleep in a bed surrounding environment by using a millimeter wave radar, and positioning a thoracic cavity position by adopting spatial two-dimensional analysis; the problem that interference exists in radar sign signal extraction of different targets at the same distance is solved. And a respiration signal Shannon entropy is constructed as an iterative index of the whale optimization algorithm, and the index is minimized to realize iterative optimization of variational mode extraction parameters, so that different respiration states are matched with different parameters, and thus a dominant frequency narrowband respiration signal is accurately extracted. A breathing time-frequency energy diagram obtained by data processing is used as input, and a CNN network and a bidirectional long-short-term memory module are used together to construct a feature extraction module, so that the method can recognize the change trend of frequency along with time, capture more comprehensive features, and recognize target sleep apnea more accurately. In addition, the hybrid network enables accurate classification of unmanned scenarios, apnea, hypopnea, and normal respiration.

The invention provides a large-load industrial-grade humanoid robot upper half body module and a humanoid robot, and belongs to the technical field of robots. The large-load industrial-grade humanoid robot upper half body module comprises a head, an upper half body, a left arm and a right arm; the left side and the right side of the square chest upper body are rotationally connected with a left arm and a right arm respectively, and the square chest upper body comprises a chest structure, a waist structure, a waist rotation driving joint, a waist joint mounting part, a body binocular depth camera, a camera radar mounting part, a 360-degree laser radar, a camera mounting part and a robot battery system; the robot upper body module can be operated in multiple directions, and the flexibility and adaptability of the robot upper body module are improved; the thoracic cavity structure is stably made of plates and connected through tenons and bolts, higher rigidity and strength can be provided, and the overall weight and the machining difficulty of the thoracic cavity structure can be effectively reduced on the premise that the load weight is guaranteed.

The invention relates to a biological feedback training device for swallowing and breathing cooperative training, which comprises a throat myoelectricity acquisition device for monitoring throat surface myoelectricity of a patient, a thoracic cavity contraction and expansion sensing device for monitoring breathing actions of the patient and a processing device for cooperative control. The patient is prompted to carry out swallowing actions in a specific stage of the breathing process in a biological feedback mode, the biological feedback training device can effectively train swallowing and breathing capacities of the patient, and the risk of aspiration of the patient is reduced.

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 relates to the technical field of vehicle safety evaluation, in particular to a finite element model modeling method capable of reproducing chest torsion performance. Comprising the steps that the geometric contour of a thoracic cavity is extracted through a lying posture tomography image, the thoracic cavity structure comprises a sternum structure, a thoracic vertebra structure and a rib structure, the lobe posterior angle of the thoracic vertebra is corrected based on a standing posture X-ray computed tomography image, and a three-dimensional geometric model of the thoracic cavity is reconstructed; establishing a thoracic cavity finite element model through grid division and material attribute definition; establishing a spherical hinge between the thoracic vertebra transverse process and the rib head; assembling the thoracic cavity finite element model into a whole person element model; and carrying out parameterized model optimization. According to the technical scheme, the real anatomical structure and the chest response data of the multi-direction complex collision working condition can be combined to establish the high-biological fidelity finite element model capable of reproducing the chest torsion performance, so that the chest injury condition in the VRU traffic accident can be predicted more accurately.

The invention relates to a breathing heart rate detection method and device based on an FMCW radar, and belongs to the technical field of signal processing.The breathing heart rate detection method based on the FMCW radar comprises the steps that FMCW radar detection signals are preprocessed, and thoracic cavity phase signals are obtained; performing time sequence data decomposition on the thoracic cavity phase signals, and determining a target signal from the thoracic cavity phase signals after time sequence data decomposition based on the reference range of the respiratory frequency and the heartbeat frequency of the target population; performing multi-scale decomposition on the target signal, and separating a target respiration signal and a target heartbeat signal from the target signal; and based on a spatial spectrum estimation algorithm, determining the breathing frequency and the heartbeat frequency of the to-be-detected person from the target breathing signal and the target heartbeat signal. According to the method, the respiratory heart rate detection is realized, the influence of noise on the detection result is reduced, and the accuracy of the respiratory heart rate detection is further improved.

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.

Devices, systems, and methods described in this disclosure can be used to deliver electroporation and adjunct therapies to treat anastomotic leaks and the resulting abscess cavities around the GI tract, within the thoracic cavity, and elsewhere within the human body. The thermal or non-thermal electroporation therapy can be delivered using the devices, systems, and methods described herein. In some embodiments, the electroporation energy is delivered to achieve sterilization and promote healing of spaces such as abscess cavities.

The invention relates to the technical field of medical training equipment, and particularly discloses a training device for trauma first aid simulation, which comprises a thoracic cavity model and further comprises a mounting cavity, and the mounting cavity is formed in the thoracic cavity model; the pressing assembly is mounted in the chest model; the driving assembly is installed on one side of the pressing assembly, the driving assembly moves when the pressing assembly acts, the detection block is fixed to the driving assembly, and the driving assembly drives the detection block to move synchronously when moving; the detection assembly is installed at the end of the driving assembly, whether the pressing force is appropriate or not is judged by observing whether a detection block normally makes contact with the detection assembly or not and the change of the force feedback assembly, the pressing force of the user is adaptively adjusted according to the trained result, and therefore targeted training is conducted according to the trained result; the training efficiency of trainees can be effectively improved, so that the trainees can train proper pressing force in a short time.

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 thoracocentesis tube capable of monitoring the chest pressure in real time comprises a main body assembly, and the main body assembly comprises a chest drainage tube, a medicine conveying hole, a medicine conveying tube, a three-way connector and an anti-blocking hole. The medicine conveying tube, the chest pressure detection connector, the medicine feeding connector and the like are integrated on the chest drainage tube, so that medical staff can monitor the pressure and the blood oxygen concentration in the chest in real time while conducting closed drainage treatment on the chest, medicine is directly and accurately fed into the chest through the medicine feeding connector when necessary, extra operation and equipment are not needed, and the operation is convenient. Convenience and efficiency of clinical treatment are greatly improved, pain and infection risks of patients are reduced, and rapid recovery of the patients is facilitated; the pressure change and the blood oxygen concentration change in the thoracic cavity are sensed in real time through the detection equipment, continuous and dynamic monitoring of the pressure and the blood oxygen concentration in the thoracic cavity in the whole drainage process is achieved, instant and accurate pressure data are provided for medical staff, and the medical staff can find the abnormal change of the pressure in the thoracic cavity in time.

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 discloses a diaphragm motion state monitoring device and a breathing health assessment method. The device comprises a wearable equipment body, a pair of flexible pressure sensors, a flexible myoelectricity sensor and a main control unit, the wearable equipment body is rectangular, the pair of flexible pressure sensors are arranged on the upper portion and the lower portion of the wearable equipment body, the flexible myoelectricity sensor is arranged between the pair of flexible pressure sensors, and the main control unit is arranged outside the wearable equipment body; the pair of flexible pressure sensors is used for detecting a thoracic cavity pressure signal and an abdominal cavity pressure signal; the flexible myoelectricity sensor is used for detecting diaphragm myoelectricity signals; and the main control unit is used for performing index calculation based on the processed chest pressure signal, abdominal pressure signal and diaphragm electromyographic signal to obtain a plurality of respiratory health indexes, and sending the indexes to the mobile terminal for comparison so as to realize respiratory health assessment. According to the invention, real-time monitoring and evaluation of the breathing health state of the user can be realized.

The present invention discloses a non-contact real-time physiological sign monitoring system based on millimeter wave radar, comprising a millimeter wave radar and a plurality of modules for processing radar signals, wherein the millimeter wave radar is configured to continuously transmit electromagnetic wave signals, and simultaneously receive echo signals and perform frequency mixing processing on the echo signals to obtain intermediate frequency signals, and the intermediate frequency signals are processed to obtain a radar four-dimensional data matrix; the human body's physiological signs are monitored by analyzing the human body's chest micro-motion information in the signals through each module; a constant false alarm rate detection algorithm is used to process the target echo and filter out invalid signals; an adaptive distance unit selection algorithm based on the short-term stability of a respiratory signal is used to accurately capture the radar echo reflecting the human body's physiological movement; a variational mode decomposition algorithm is used to process the mixed human body physiological sign signal obtained by the processing, and a gray wolf optimization algorithm is used to optimize the key parameters in the variational mode decomposition to obtain a more accurate estimation of physiological sign parameters.

The invention provides a non-contact heart sound monitoring method and system, a terminal and a medium, and particularly relates to the technical field of biomedical engineering.The non-contact heart sound monitoring method comprises the steps that lasers of different wavebands are used for conducting multi-point synchronous monitoring on the heart, and a defocus speckle image is obtained; performing signal extraction on the out-of-focus speckle image to obtain heart movement signals corresponding to multiple wavebands; and filtering the heart movement signals corresponding to the multiple wavebands to obtain heart sound signals. According to the scheme, the characteristic of out-of-focus independent interference imaging of the multi-band laser is utilized, multi-point synchronous monitoring is carried out on micro movement of the heart position in the thoracic cavity through the laser of different bands, the heart sound can be monitored in a non-contact mode, the requirement for measuring environment noise can be lowered, meanwhile, the detection precision is guaranteed, and the detection efficiency is improved. And the comfort of the target living body can be improved.

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.