760 results about "Thoracic cavity" patented technology

The invention relates to the technical field of physiological information monitoring, in particular to a non-contact vital sign data monitoring method and system.The non-contact vital sign data monitoring method comprises the following steps that on the basis of a millimeter wave radar sensor, thoracic cavity micro-motion data of a target individual are collected in real time, thoracic cavity motion signals caused by heartbeat and respiration are separated, and the respiration frequency and change are recognized; and breathing mode data is obtained. According to the method, chest micro-motion and infrared radiation data of a target individual are collected and analyzed in real time through a millimeter wave radar sensor and an infrared sensor, accurate monitoring of vital signs is achieved, the abnormal detection threshold value is adjusted in combination with the physiological state of the individual, and the monitoring result fits the actual health condition of the individual; through joint analysis of a plurality of vital signs, comprehensive evaluation of the health state is realized, in combination with health trend prediction, data support is provided for preventive health management and early disease diagnosis, the practicability of a monitoring system is improved, and the application range of a non-contact monitoring technology in a complex environment is expanded.

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 relates to the technical field of respiratory training, in particular to a respiratory muscle training system based on thoracic induction, which comprises a thoracic dynamic monitoring module, a respiratory muscle state recognition module, a fatigue judgment and adjustment module, a training control module and a task construction module. According to the method, through combined extraction of capacitance sensing data of chest expansion change, a vertical displacement trend and chest pressure floating, the reduction precision of a real respiration traction process is effectively improved, a time axis is used as a unified reference, different types of sensing data are synchronously analyzed, the respiration traction judgment accuracy is remarkably improved, and the method is suitable for popularization and application. The probability of misjudgment caused by electromyography and body movement dislocation is eliminated, the capacity of capturing the participation state of respiratory muscles is enhanced, the variation trend between electromyography response and traction starting is tracked and captured through the time difference of continuous periods, the training execution accuracy is improved, the intervention targeting is recovered, and the training efficiency is improved. And leap-over improvement is realized in the aspects of multi-source information collaborative identification and training personalized adjustment.

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.

A patient monitoring system for improved thoracic fluid measurement from a patient is provided. The system includes therefrom. The system also includes a remote server including a memory and a processor configured to receive the RF value(s), retrieve weighting parameter(s), and apply the weighting parameter(s) to the RF value(s) to determine and output an amount of thoracic fluid. The weighting parameter(s) is determined by a clinical modality process including receiving reference thoracic fluid information for a patient population, producing RF-based thoracic fluid information for the patient population, and deriving the weighting parameter(s) by optimizing an association of the RF-based thoracic fluid information with the reference thoracic fluid information.

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 discloses a venous thrombosis risk assessment method based on a large language model, and relates to the technical field of medical artificial intelligence, and the method comprises the steps: collecting thoracic surgery diagnosis and treatment data of a patient, carrying out the space-time alignment, generating a standard diagnosis and treatment data flow, and carrying out the homomorphic encryption of the standard diagnosis and treatment data flow, and forming an encrypted patient data package; inputting the encrypted patient data packet into a multi-task large language model, performing feature extraction and semantic coding by a feature coding layer, performing time sequence modeling and risk probability calculation by a risk quantification layer, and outputting a venous thromboembolism risk level of a patient; and performing feature decoupling and potential space mapping on the encrypted patient data packet to obtain thrombus semantic potential features. Through the multi-task large language model, the dual machine learning algorithm and the homomorphic encryption, the accuracy of venous thrombosis risk early warning is improved, and the safety of the risk assessment process is enhanced.

The speed-adjustable negative pressure drainage device comprises a drainage tube, a bottle body, a cover body and a negative pressure source connector, the cover body is rotated to drive a top ring cambered surface protrusion to jack up a bead body, a through hole is opened according to the angle gradient, external air enters dilution negative pressure, and linear speed regulation without negative pressure source adjustment is achieved; the bead body periodically opens and closes the through holes to form pulsating type instantaneous suction force, so that the adhesive force between blood clots and the tube wall is destroyed, and blockage is actively prevented; the gradient section of the drainage tube accelerates liquid flow through abrupt drop to generate local negative pressure to pull rear liquid flow; the upper convex hulls enlarge the sectional area of a pipe cavity before sharp drop, decelerate liquid flow and form a vortex region, so that blood clots are separated and deposited due to inertia, and liquid-solid layering is realized; the device has the functions of mechanical blockage prevention, precise pressure control and overload protection, the clinical blockage rate is reduced from 30% to 5% or below, power support is not needed, the device is suitable for postoperative drainage scenes such as the abdominal cavity and the thoracic cavity, and the medical operation load and the complication risk of a patient are remarkably reduced.

The invention belongs to the technical field of effusion drainage, and provides a peritonitis pleural effusion drainage device which comprises an effusion storage box and a puncture needle, the puncture needle is connected with the effusion storage box through a drainage tube, the interior of the effusion storage box is divided into an upper cavity and a lower cavity, and the cavity located on the lower side is divided into a first containing cavity and a second containing cavity which are arranged left and right; the liquid storage tank is provided with a first connecting pipe and a second connecting pipe which are respectively communicated with the first placing cavity and the second placing cavity, and the first connecting pipe and the second connecting pipe are respectively connected with a test tube and a flushing structure for extracting antibiotics; by arranging the speed regulating structure, adverse effects on a patient caused by too high ascites flow speed are avoided; by arranging the fixing cylinder, the end of the drainage tube and the liquid storage bag can be conveniently and firmly installed, and the situation that the liquid storage bag falls off during shaking, and environmental pollution is caused is avoided; a liquid outlet cover is arranged, so that medical workers can conveniently and quantitatively take out ascites for detection.

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.

The invention provides a thoracic cavity closed drainage puncture outfit and a use method thereof.The outer wall of the bottom end of a drainage tube is evenly provided with a plurality of drainage grooves penetrating through the inner wall, the outer wall of the top end of the drainage tube is fixedly connected with a fixing valve, the top end of the drainage tube is fixedly connected with a three-way valve, and an inner core is arranged in the drainage tube; the inner core comprises a puncture needle head positioned in the bottom end of the drainage tube; the top of the puncture needle head extrudes the drainage fin, so that the middle of the drainage fin protrudes outwards to support peripheral tissues, and after the middle of the drainage fin protrudes outwards, on one hand, a fixing effect can be achieved, on the other hand, the drainage groove can be prevented from being blocked, and the problem of unsmooth drainage is effectively avoided; meanwhile, the puncture needle head completely retracts into the drainage tube, so that secondary injury of the puncture needle head to a patient can be effectively avoided, drainage and puncture operation can be completed at a time, and pain of the patient can be reduced.

A traction device comprising: a bed frame with a bed board placed on top of the bed frame, the bed board includes four bed board sections: wherein the first bed board section is movable, featuring an ergonomic cervical cushion, a head fixing device that fully encloses the head, and a chin strap; the second bed board section is fixed, equipped with multiple stoppers that are adjustable according to the users body shape, including shoulder stoppers for counteracting cervical traction and armpit stopper shafts for counteracting thoracic and lumbar traction; the third bed board section is movable, featuring an ergonomic lumbar cushion and iliac stoppers that are adjustable according to the users body shape; and the fourth bed board section is movable, with multiple foot fixing devices composed of an upper part shaped to the arc of the dorsum of the foot and a lower part shaped to the arc of the heel.

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.