Respiration auxiliary regulation and control method, system and equipment

Abstract

The invention discloses an auxiliary respiration regulation and control method, system and equipment, and relates to the technical field related to medical equipment control, and the method comprises the following steps: activating a predetermined locator to dynamically monitor and obtain a target chest position of a target user; carrying out electromagnetic wave emission based on the target thoracic cavity position, and obtaining a target echo signal of the target user; introducing a predetermined filter to filter the target echo signal to obtain a target respiration signal; dynamically monitoring to obtain a target diaphragm electrical activity signal, and cooperating with a target respiration signal to perform auxiliary regulation and control optimization analysis to obtain an optimal auxiliary pressure scale factor; and according to the optimal auxiliary pressure scale factor, performing breathing auxiliary regulation and control on the target user. The technical problems that in the prior art, parameters of breathing auxiliary equipment are fixed, the breathing auxiliary equipment cannot be accurately matched with the individual physiological state, and consequently the accuracy and effectiveness of breathing auxiliary regulation and control are insufficient are solved, and the technical effects that accurate breathing auxiliary regulation and control are achieved, and the safety and effectiveness of breathing auxiliary regulation and control are improved are achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to medical device control, and specifically to respiratory assistance control methods, systems and equipment. Background Art

[0002] Respiratory assistance is the key to ensuring the respiratory function of patients with respiratory diseases, postoperative rehabilitation patients and workers in special environments. Traditional respiratory assistance equipment, such as ventilators, usually adopts ventilation modes with fixed parameters, which are difficult to accurately adapt to the respiratory needs of different individuals in different physiological states, and difficult to accurately capture the physiological signals of the user during breathing. It is impossible to perceive the subtle changes in the user's chest cavity and the actual activity status of the diaphragm in real time, resulting in the assistance pressure being too high or too low. Excessive pressure can easily cause adverse reactions such as barotrauma and human-machine confrontation, increasing patient pain and treatment risks; too low pressure cannot provide effective respiratory support, affecting the effectiveness and safety of respiratory assistance treatment.

[0003] Therefore, in the current related technologies, there are technical problems that the parameters of respiratory assistance equipment are fixed and cannot accurately adapt to the individual's physiological state, resulting in insufficient accuracy and effectiveness of respiratory assistance control. Summary of the Invention

[0004] This application solves the technical problems in the prior art that the parameters of respiratory assistance equipment are fixed and cannot accurately adapt to the individual's physiological state, resulting in insufficient accuracy and effectiveness of respiratory assistance control, by providing a respiratory assistance control method, system and equipment. It achieves the technical effect of realizing precise respiratory assistance control and improving the safety and effectiveness of respiratory assistance control.

[0005] The present application provides a respiratory assistance control method, which includes: activating a predetermined locator to dynamically monitor and obtain a target chest position of a target user; emitting electromagnetic waves based on the target chest position, and obtaining a target echo signal of the target user; introducing a predetermined filter to filter the target echo signal to obtain a target respiratory signal; dynamically monitoring and obtaining a target diaphragm electrical activity signal of the target user, and performing auxiliary control optimization analysis in conjunction with the target respiratory signal to obtain an optimal auxiliary pressure proportional factor; and performing respiratory assistance control on the target user according to the optimal auxiliary pressure proportional factor.

[0006] In a possible implementation, the breathing assistance control method further performs the following processing: monitoring the target user through the optical camera positioning component in the predetermined locator to obtain a target optical image; reading the predetermined joint position, and marking the predetermined joint position in the pre-processed target optical image to obtain a target marked image; analyzing the target marked image to determine the target chest position; wherein the predetermined joint position includes at least the shoulder position, chest position and waist position.

[0007] In a possible implementation, the respiratory assistance control method further performs the following processing: acquiring the target infrared radiation of the target user through the thermal imaging positioning component in the predetermined locator; drawing a target thermal image based on the target electrical signal obtained by converting the target infrared radiation; and analyzing the target thermal image to determine the target chest position.

[0008] In a possible implementation, the breathing assistance control method further performs the following processing: the predetermined locator dynamically monitors the target user based on a predetermined frequency.

[0009] In a possible implementation, the respiratory assistance control method further performs the following processing: extracting the passband threshold stored in the memory of the predetermined filter; performing preliminary screening processing on the target echo signal using the passband threshold as a screening constraint to obtain an initial respiratory signal; performing modal decomposition on the initial respiratory signal to obtain a signal decomposition result, wherein the signal decomposition result includes a first modal component; comparing the first modal component with the initial respiratory signal to obtain a first value index; when the first value index reaches a predetermined value index threshold, adding the first modal component to the target respiratory signal.

[0010] In a possible implementation, the respiratory assistance control method further performs the following processing: obtaining a first characteristic quantity of the first modal component; and taking the ratio of the first characteristic quantity to the total characteristic quantity of the initial respiratory signal as the first value index.

[0011] In a possible implementation, the respiratory assistance control method also performs the following processing: determining the target respiratory index of the target user; using the target diaphragm electrical activity signal and the target respiratory signal as simulation constraints, performing simulation analysis on the first auxiliary pressure proportional factor of the target user to obtain first simulation information; reading a predetermined respiratory index, and traversing the first simulation information to obtain a first simulated respiratory index; when the first simulated respiratory index reaches the target respiratory index, adding the first auxiliary pressure proportional factor to a candidate list; taking the auxiliary pressure proportional factor corresponding to the maximum index in the candidate list as the optimal auxiliary pressure proportional factor.

[0012] In a possible implementation, the breathing assistance control method further performs the following processing: collecting multi-dimensional user feature parameters of the target user to form a target feature set; performing weighted calculation on the target feature set to obtain a target individual coefficient; and adaptively adjusting the baseline breathing index based on the target individual coefficient to obtain the target breathing index.

[0013] The present application also provides a respiratory assistance control system, which includes: a target chest position acquisition unit, which is used to activate a predetermined locator to dynamically monitor and obtain the target chest position of the target user; a target echo signal acquisition unit, which is used to emit electromagnetic waves based on the target chest position and obtain the target echo signal of the target user; a target breathing signal acquisition unit, which is used to introduce a predetermined filter to filter the target echo signal to obtain a target breathing signal; an auxiliary control optimization analysis unit, which is used to dynamically monitor and obtain the target diaphragm electrical activity signal of the target user, and perform auxiliary control optimization analysis in conjunction with the target breathing signal to obtain an optimal auxiliary pressure proportional factor; a respiratory assistance control unit, which is used to perform respiratory assistance control on the target user according to the optimal auxiliary pressure proportional factor.

[0014] The present application also provides an electronic device, comprising: a memory for storing executable instructions; and a processor for implementing a breathing assistance control method when executing the executable instructions stored in the memory.

[0015] The respiratory assistance control method, system and device proposed in this application are intended to activate a predetermined locator to dynamically monitor the target chest position of the target user; transmit electromagnetic waves based on the target chest position and obtain the target echo signal of the target user; introduce a predetermined filter to filter the target echo signal to obtain the target respiratory signal; dynamically monitor the target diaphragm electrical activity signal, and perform auxiliary control optimization analysis in conjunction with the target respiratory signal to obtain the optimal auxiliary pressure proportional factor; and perform respiratory assistance control on the target user based on the optimal auxiliary pressure proportional factor. This solves the technical problem in the prior art that the parameters of respiratory assistance equipment are fixed and cannot accurately adapt to the individual's physiological state, resulting in insufficient accuracy and effectiveness of respiratory assistance control, and achieves the technical effect of realizing precise respiratory assistance control and improving the safety and effectiveness of respiratory assistance control. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0017] Figure 1 A flow chart of the respiratory assistance control method provided in an embodiment of the present application.

[0018] Figure 2 Schematic diagram of the respiratory assistance control system structure provided in an embodiment of the present application.

[0019] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application

[0020] Explanation of the accompanying symbols: target chest position acquisition unit 10, target echo signal acquisition unit 20, target respiratory signal acquisition unit 30, auxiliary control optimization analysis unit 40, respiratory auxiliary control unit 50, input device 401, processor 402, memory 403, output device 404. DETAILED DESCRIPTION

[0021] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0022] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0023] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0024] The present application provides a method for assisting breathing control, such as Figure 1 As shown, the method includes:

[0025] Step S100: activating a predetermined locator to dynamically monitor and obtain a target chest position of a target user.

[0026] Preferably, the position, shape and dynamic changes of the target user's chest cavity are captured and monitored in real time by the optical camera positioning component and the thermal imaging positioning component included in the predetermined locator to obtain accurate chest cavity position data, wherein the optical camera positioning component is used to monitor the mechanical movement characteristics of the chest wall during breathing. Specifically, the optical camera positioning component collects images of the target user's chest area through an optical camera (such as a high-definition camera, an infrared camera, etc.), and uses computer vision algorithms (such as image recognition, edge detection, three-dimensional reconstruction, etc.) to analyze the chest contour, fluctuation amplitude, motion trajectory and other characteristics. For example, the spatial position of chest anatomical structures such as the sternum and ribs is identified to determine the reference position of the chest cavity; the expansion and contraction amplitude of the chest cavity during breathing (such as the maximum range of outward expansion of the chest cavity during inhalation and the degree of retraction during exhalation), movement frequency (respiratory frequency) and symmetry (whether the chest cavity movements on both sides are consistent) are tracked; and the morphological changes of the chest cavity are intuitively reflected.

[0027] Preferably, the thermal imaging positioning component is based on infrared thermal imaging technology. It detects the thermal radiation signal on the surface of the chest skin through sensors, generates thermal images, and analyzes the temperature distribution and change patterns in different areas. It is used for covert monitoring of long-term bedridden patients or those wearing respiratory assistance equipment. Among them, infrared thermal imaging can penetrate clothing for non-contact monitoring and is not affected by light conditions. Specifically, thermal imaging captures the contraction and relaxation of chest muscles (such as intercostal muscles) during breathing, which is accompanied by fluctuations in skin surface temperature caused by changes in metabolic activity, indirectly reflecting the intensity and rhythm of respiratory movements; if there is local inflammation, abnormal blood circulation or muscle dysfunction in the chest cavity, abnormal temperature distribution (such as local temperature increase or decrease) may appear in the thermal imaging image, which assists in locating the abnormal position.

[0028] Preferably, the optical camera positioning component and the thermal imaging positioning component work synchronously to continuously collect chest images and thermal signal data during the target user's breathing cycle to form a dynamic sequence that changes over time. Specifically, by combining the spatial position information of the optical image and the functional status information of the thermal imaging, the real-time position of the chest in three-dimensional space (such as changes in the anterior-posterior diameter and left-right diameter) and the physiological activity state (such as breathing depth and muscle engagement) can be more comprehensively determined; at the same time, optical camera and thermal imaging complement each other. For example, the optical image can calibrate the spatial positioning error of the thermal imaging, and the thermal signal can assist in analyzing the muscle movement intensity that is difficult to directly judge in the optical image. Finally, the output includes comprehensive data including spatial coordinates (such as three-dimensional position parameters), motion parameters (such as breathing amplitude and frequency), and physiological parameters (such as local temperature change trends), so as to achieve multi-dimensional, dynamic and accurate capture of the target chest position.

[0029] Furthermore, step S100 also includes step S110, monitoring the target user through the optical camera positioning component in the predetermined locator to obtain a target optical image; step S120, reading the predetermined joint position, and marking the predetermined joint position in the preprocessed target optical image to obtain a target marked image; step S130, analyzing the target marked image to determine the target chest position; wherein the predetermined joint position includes at least the shoulder position, the chest position and the waist position.

[0030] Preferably, the optical camera positioning component (such as a high-definition camera, a depth camera, etc.) in the predetermined locator is used to monitor the target user to obtain a target optical image, that is, the upper body of the target user is photographed in real time, and a continuous optical image sequence (i.e., video frames) including the chest area is obtained, which includes the spatial position and morphological information of the user's chest, shoulders, waist and other parts, and the predetermined joint positions are read, including the shoulder position, chest position and waist position, wherein the shoulder position refers to the spatial coordinates of the bilateral acromion (the highest point of the shoulder) or the acromioclavicular joint, the chest position refers to the sternal angle (the connection between the sternal manubrium and the body), the midpoint of the nipple line and other landmark anatomical positions of the chest, and the waist position refers to the coordinates of the bilateral iliac crests (upper edge of the pelvis) or the lumbar spinous process; then the target optical image is preprocessed, specifically including grayscale conversion, noise reduction (such as Gaussian filtering), contrast enhancement, etc. of the original target optical image to improve the image quality.

[0031] Preferably, a computer vision algorithm (such as OpenPose, MediaPipe and other human pose estimation models) or an image processing method (such as template matching, feature point detection) is then used to identify and extract the pixel coordinates of predetermined joints in the preprocessed image, and the position of each joint is marked on the image with specific marks (such as colored dots, connecting lines) to form a visual annotated image. For example, red dots are used to mark the shoulders, green dots are used to mark the chest, and blue dots are used to mark the waist; the marked points on both sides of the shoulders, chest, and waist are then connected to form the outline framework of the upper body.

[0032] Preferably, the target annotated image is analyzed to determine the target chest position. Specifically, based on the annotated joint positions, the image area is divided into the head area (above the shoulder line), the upper chest area (between the shoulder and chest lines), and the lower chest and abdomen area (between the chest and waist lines). At the same time, the chest boundary is precisely located. For example, the area extending downward by a certain proportion (e.g., 30%) of the bilateral shoulder lines is used as the horizontal boundary, and the area extending upward and downward by a certain distance (e.g., 15 cm) of the chest marker points is used as the vertical boundary. The specific distance is adjusted according to the human body proportions or user preset parameters. In addition, during the user's breathing process, the chest will move up and down and forward and backward with the breathing movement. By continuously analyzing multiple frames of annotated images, the displacement vector of the chest area is calculated, and the chest position is updated in real time to ensure positioning accuracy. By marking key joints such as the shoulders, chest, and waist, a human structural framework is established to avoid positioning errors caused by relying solely on image features (such as skin color and texture). At the same time, when the user's body position changes (such as sitting, standing, lying on the side) or makes small movements, the relative relationship of the joint positions remains stable, and the chest positioning can be quickly adjusted to ensure that the respiratory assistance equipment continues to be aimed at the target area, thereby achieving automated and standardized positioning of the target user's chest position.

[0033] Furthermore, step S100 also includes step S140, obtaining the target infrared radiation of the target user through the thermal imaging positioning component in the predetermined locator; step S150, drawing a target thermal image based on the target electrical signal obtained by converting the target infrared radiation; step S160, analyzing the target thermal image to determine the target chest position.

[0034] Preferably, a thermal imaging positioning component (infrared thermal imager, thermal sensor array, etc.) in a predetermined locator is used to monitor infrared radiation of different intensities (the higher the temperature, the greater the radiation intensity) generated by metabolic activities and blood circulation differences in various parts of the human body. Among them, the surface skin temperature of the chest area (covering the heart and lungs) is usually higher than that of some areas of the back or abdomen due to organ activities and blood vessel distribution, and respiratory movements may be accompanied by local temperature fluctuations (such as expansion of the chest wall during inhalation, and local blood flow changes may cause slight temperature changes). The thermal imaging component scans the torso of the target user (with an emphasis on the chest and abdomen), collects the infrared energy radiated from its surface, and forms original thermal signal data.

[0035] Preferably, the infrared radiation intensity received is converted into a target electrical signal (voltage or current value) by an infrared detector (such as a microbolometer) inside the thermal imaging component. The signal intensity is positively correlated with the surface temperature of the object, that is, areas with higher temperatures (such as the infraclavicular fossa and the precordial area) correspond to stronger electrical signals, and areas with lower temperatures (such as the intercostal space and the abdominal fat layer) correspond to weaker electrical signals. The target electrical signal is then processed by signal amplification and analog-to-digital conversion (A / D conversion) and mapped into grayscale values or pseudo-color values of image pixels (such as cold colors represent low temperatures and warm colors represent high temperatures), and finally a target thermal image is generated, in which the chest area may present a relatively uniform warm-toned area in front of the sternum and below the clavicle (compared with the surrounding skin) due to the heart beat and lung respiratory movement. The shoulder muscles are thicker and more active, and may present a higher temperature. The waist (especially the lumbar spine area) may have a lower temperature than the chest due to the distribution of bones and fat.

[0036] Preferably, the target thermal image is analyzed to determine the target chest location. Specifically, by setting a temperature threshold (e.g., above 34°C), high-temperature areas are extracted from the thermal image. The temperature of the chest surface (covering the heart and large blood vessels) is generally higher than that of the back muscles or abdominal fat, and the high-temperature area is initially located within the chest area. For example, if the temperature near the sternum in the target thermal image is 35°C and the temperature of the abdomen is 33°C, the chest area can be segmented using a threshold of 34°C. During inhalation, the expansion of the chest cavity causes the chest wall skin to stretch, which may increase local blood flow and cause a slight temperature rise. During exhalation, the chest wall retracts and the temperature drops slightly. By analyzing a series of continuous thermal images, areas that fluctuate regularly with the respiratory cycle can be identified, further confirming the chest location. Edge detection (e.g., the Canny operator) can also be used to identify boundaries with obvious temperature gradients in thermal images (e.g., the temperature boundary between the chest and abdomen), or morphological operations (dilation, erosion) can be used to fill in areas with uniform temperature to determine the chest contour. Thermal imaging positioning is used to achieve non-contact, functional positioning of the chest cavity, which is suitable for complex environments or special populations, ensuring the accuracy and adaptability of respiratory assistance control.

[0037] Furthermore, step S100 also includes that the predetermined locator dynamically monitors the target user based on a predetermined frequency.

[0038] Preferably, the predetermined locator dynamically monitors the target user based on a predetermined frequency, wherein the predetermined frequency refers to the number of times the locator (such as an optical camera, a thermal imaging sensor) collects data per second (unit: Hz). For example, the optical component collects images at 30Hz (30 frames per second), and the thermal imaging component monitors thermal signals at 10Hz. The higher the frequency, the denser the data points acquired per unit time, and the more accurate the capture of rapid movements (such as the high-frequency fluctuations of the chest during intense breathing), ensuring continuous position tracking and monitoring of individuals in motion, and avoiding random interruptions in data collection through periodic sampling at a fixed frequency, ensuring the continuity of the monitoring signal, and thus providing continuous dynamic respiratory assistance control data.

[0039] Step S200: transmitting electromagnetic waves based on the target chest position, and acquiring a target echo signal of the target user.

[0040] Preferably, the target user's echo signal is acquired through electromagnetic wave detection (such as millimeter wave radar, microwave radar, etc.). Specifically, based on the target chest position (determined by the locator), electromagnetic waves of a specific frequency (such as 24GHz millimeter waves) are emitted. The electromagnetic beam is focused on the chest area and reflected by the tissue within the chest (such as lung gas, blood, and muscle). Part of the reflected wave returns to the receiving end to form an echo signal. The dielectric constant of the air-containing lung tissue and the surrounding soft tissue differ significantly, resulting in a high reflection coefficient and a strong echo signal. The locator provides the target chest position in real time, such as three-dimensional coordinates (x, y, z). The electromagnetic wave transmission module adjusts the beam direction and position based on this position to ensure that the electromagnetic beam is always focused on the central area of the chest. For example, if the locator detects that the user has changed from a sitting position to a standing position and the chest has moved up 50 cm, the transmission module will synchronously adjust the antenna elevation angle or the position of the robotic arm to keep the beam aligned with the chest. The transmission power is dynamically adjusted according to the distance between the chest and the transmission source (e.g., the power is increased as the distance increases) to ensure stable echo signal strength.

[0041] Step S300: introducing a predetermined filter to filter the target echo signal to obtain a target breathing signal.

[0042] Preferably, signal filtering is performed through a predetermined filter to extract a target respiratory signal from the target echo signal, wherein the target respiratory signal includes an effective respiratory signal and an interference signal. The effective respiratory signal is the change in electromagnetic wave reflection caused by chest movement, which is manifested as a low-frequency, periodic signal with a frequency range of usually 0.1-0.5Hz (corresponding to a respiratory rate of 6-30 times / minute). The interference signal refers to environmental noise (50 / 60Hz power frequency interference, electromagnetic wave multipath reflection, etc.) and physiological noise (heartbeat 0.8-2Hz, random body micro-movements such as talking, swallowing, and gastrointestinal peristalsis 0.05-0.3Hz); the predetermined filter retains the respiratory signal frequency band (0.1-0.5Hz) by configuring a specific frequency response, suppresses noise in other frequency bands, effectively separates the respiratory signal from the noise, and thereby improves the signal-to-noise ratio (SNR) of the respiratory signal, highlights the characteristics of the respiratory cycle, such as the inhalation peak and the expiratory trough, and finally obtains the target respiratory signal, and ensures the accuracy and effectiveness of respiratory monitoring.

[0043] Furthermore, step S300 also includes step S310, extracting the passband threshold stored in the memory of the predetermined filter; step S320, using the passband threshold as a screening constraint, performing preliminary screening processing on the target echo signal to obtain an initial breathing signal; step S330, performing modal decomposition on the initial breathing signal to obtain a signal decomposition result, wherein the signal decomposition result includes a first modal component; step S340, comparing the first modal component with the initial breathing signal to obtain a first value index; step S350, when the first value index reaches a predetermined value index threshold, adding the first modal component to the target breathing signal.

[0044] Preferably, a passband threshold stored in the memory of a predetermined filter is extracted, wherein the passband threshold refers to the amplitude threshold of the frequency range in which the signal is allowed to pass in the predetermined filter, that is, the highest effective frequency within the transmission range (passband cutoff frequency), which is used to distinguish effective respiratory signals from noise. The passband threshold is used as a screening constraint to perform preliminary screening processing on the target echo signal, eliminate noise that obviously exceeds the respiratory frequency range (such as limb movement signals higher than 1 Hz or baseline drift lower than 0.05 Hz), and retain the effective signal within the passband threshold as the initial respiratory signal.

[0045] Preferably, a non-parametric signal decomposition method such as empirical mode decomposition (EMD) or variational mode decomposition (VMD) is then used to perform modal decomposition on the initial respiratory signal, decomposing the initial respiratory signal into multiple intrinsic modal components, that is, obtaining a signal decomposition result, so as to separate components directly related to respiratory motion (such as low-frequency components corresponding to periodic chest fluctuations) from the mixed signal, and at the same time separate interference components (such as high-frequency or non-periodic components corresponding to heartbeats and random micro-motions); wherein the first modal component is any modal component in the signal decomposition result, and then The first modal component is compared with the initial respiratory signal, and a first value index is obtained by calculating the correlation coefficient or feature ratio between the two. This index is used to measure the contribution or similarity of the component to the original signal. For example, if the first modal component is heartbeat noise and its correlation with the initial respiratory signal is low (e.g., correlation coefficient <0.3), the value index is low. If the first modal component is the main frequency component of the respiratory signal (e.g., 0.3Hz corresponds to 18 breaths / minute), and its correlation with the initial signal is high (correlation coefficient >0.8), the value index is high. A predetermined value index threshold is set as a judgment criterion to filter out valid components that are highly correlated with the initial respiratory signal. When the first value index reaches the predetermined value index threshold, it indicates that the component is an important component of the initial signal (possibly a true respiratory signal) and is added to the target respiratory signal. If it does not reach the threshold, it indicates that the component is likely noise and is removed.

[0046] Furthermore, step S340 also includes step S341, obtaining a first characteristic value of the first modal component; and step S342, taking the ratio of the first characteristic value to the total characteristic value of the initial breathing signal as the first value index.

[0047] Preferably, multiple characteristic parameters of the first modal component are extracted, which may include amplitude (signal strength), frequency, period, energy (signal energy value), etc., and the first characteristic quantity is any one of the multiple characteristic parameters; then the characteristic parameters extracted from the initial respiratory signal are summed up to obtain the total characteristic quantity, and the characteristic quantity (such as energy) of the first modal component is compared with the total characteristic quantity of the initial signal to obtain a ratio value, i.e., a first value index, which is used to determine whether the first modal component is significant enough and whether it can represent a real respiratory signal. If the ratio is high (such as close to 1), it means that the component contains the main characteristics of the initial signal (such as the dominant frequency of the respiratory movement) and is a valid respiratory signal.

[0048] Step S400 : dynamically monitoring and obtaining the target diaphragm electrical activity signal of the target user, and performing auxiliary control optimization analysis in conjunction with the target breathing signal to obtain the optimal auxiliary pressure proportional factor.

[0049] Step S400 further includes step S410, determining the target breathing index of the target user; step S420, using the target diaphragm electrical activity signal and the target breathing signal as simulation constraints, performing simulation analysis on the first auxiliary pressure proportional factor of the target user to obtain first simulation information; step S430, reading a predetermined breathing index, and traversing the first simulation information to obtain a first simulation breathing index; step S440, when the first simulation breathing index reaches the target breathing index, adding the first auxiliary pressure proportional factor to a candidate list; step S450, taking the auxiliary pressure proportional factor corresponding to the maximum index in the candidate list as the optimal auxiliary pressure proportional factor.

[0050] Preferably, the electromyographic signal of the target diaphragm is collected through surface electrodes or implantable sensors, and its intensity is positively correlated with the contraction force of the diaphragm. The original electrical activity signal is then amplified, filtered (such as 50Hz notch filtering to remove power frequency interference), full-wave rectified and low-pass filtered (to extract the envelope) to obtain a target diaphragm electrical activity signal reflecting the intensity of diaphragm activity; then, based on the diaphragm electrical activity signal and the respiratory signal (such as chest movement amplitude, airflow signal), the target respiratory index of the target user is determined, that is, a quantitative indicator that comprehensively reflects the respiratory function, which may include respiratory rate (number of breaths per minute, times / min), tidal volume (gas volume per breath, mL), respiratory time (duration of each stage of the respiratory cycle) and diaphragm electrical activity intensity (such as Edi peak, average voltage).

[0051] Preferably, the target diaphragm electrical activity signal and the target respiratory signal are used as simulation constraints to perform a simulation analysis of the first auxiliary pressure proportional factor on the target user. Specifically, the target diaphragm electrical activity signal and the target respiratory signal are input signals, and the auxiliary pressure proportional factor is a simulation variable, which is used to adjust the output pressure of the respiratory assistance device (such as the pressure support level of the ventilator), and the value range is usually 0-1 (corresponding to 0 to 100% assistance strength); then, based on the mechanical model of the respiratory system (such as a linear elastic model), the relationship between the auxiliary pressure and the respiratory parameters is established, and the changes in respiratory parameters under different auxiliary pressures are simulated by adjusting the auxiliary pressure proportional factor, and the first simulation information is output, including the simulated respiratory signal (such as chest movement amplitude and frequency) and the simulated diaphragm electrical activity signal (such as inhalation peak), and then the auxiliary pressure proportional factor value that matches the simulation result with the target respiratory index is found.

[0052] Preferably, a predetermined respiratory index, i.e., a preset normal respiratory parameter range (such as respiratory rate 12-20 times / minute, tidal volume 5-8ml / kg, oxygen saturation ≥95%), is read to determine whether the simulation result meets the physiological requirements; then, the first simulation information is traversed, and the simulation result in which the simulated respiratory index is consistent with or close to the target respiratory index, and the simulated respiratory parameters (such as tidal volume, oxygen saturation) are within the predetermined respiratory index range is taken as the first simulated respiratory index, and when the simulation result of a certain auxiliary pressure proportional factor makes the first simulated respiratory index reach the target respiratory index, the auxiliary pressure proportional factor is added to the candidate list; finally, the auxiliary pressure proportional factor corresponding to the maximum index in the candidate list is taken as the optimal auxiliary pressure proportional factor, thereby significantly improving the safety and effectiveness of respiratory assisted therapy.

[0053] Furthermore, step S410 also includes step S411, collecting multi-dimensional user feature parameters of the target user to form a target feature set; step S412, performing weighted calculation on the target feature set to obtain a target individual coefficient; step S413, adaptively adjusting the baseline breathing index based on the target individual coefficient to obtain the target breathing index.

[0054] Preferably, multi-dimensional user characteristic parameters of the target user are collected, that is, multiple basic information related to the individual user (patient) is collected, such as age, weight, health status, etc., among which age affects physiological function (such as respiratory muscle strength, lung elasticity), too high or too low weight may change the respiratory load (such as increased breathing work in obese people), health status includes underlying diseases (such as chronic obstructive pulmonary disease, heart failure), allergic history, surgical history, etc., which directly affect respiratory function, and these parameters are integrated into a target feature set; then the target feature set is weighted and calculated to obtain a target individual coefficient. Specifically, different weights are assigned according to the degree of influence of each feature parameter on respiratory function. For example, the weight of health status is higher than age or weight. The multi-dimensional features are converted into a comprehensive value (i.e., target individual coefficient) through weighted summation, reflecting the overall influence of the individual physiological characteristics of the user on breathing.

[0055] Preferably, the baseline respiratory index refers to a pre-set universal respiratory index (such as the average respiratory rate and tidal volume of healthy people), and the target individual coefficient is used to adaptively adjust the baseline respiratory index to make it more in line with individual needs. For example, if the user is an obese patient (weight weight is high), the target individual coefficient may be greater than 1, and the baseline tidal volume is adjusted upward to compensate for the respiratory load; if the user is an elderly person (age weight is high), the baseline respiratory rate is lowered to adapt to the decline of physiological function; finally, the adjusted personalized respiratory index is used as the target respiratory index.

[0056] Step S500: performing breathing assistance control on the target user according to the optimal assistance pressure proportional factor.

[0057] Preferably, the target user is assisted in breathing according to the optimal auxiliary pressure proportional factor. Specifically, according to the optimal proportional factor, the respiratory equipment parameters are set, that is, the pressure output mode of the respiratory assistance equipment is adjusted. The respiratory equipment provides actual output pressure according to the optimal auxiliary pressure proportional factor during the exhalation phase to help the user overcome the inspiratory resistance (such as lung elastic resistance and airway resistance) and reduce the work of respiratory muscles; during the inhalation phase, the positive end expiratory pressure (PEEP) is adjusted according to the optimal auxiliary pressure proportional factor to maintain airway patency and improve gas exchange efficiency; at the same time, the user's physiological state is continuously monitored during the respiratory assistance process. Indicators (such as respiratory rate, tidal volume, blood oxygen saturation, and diaphragm electrical activity) are used to determine whether the current assistance pressure is appropriate and to dynamically adjust the respiratory pressure. For example, if the indicators show that breathing is still strenuous (such as too fast respiratory rate or increased diaphragm electrical activity), the assistance pressure proportional factor is increased to increase the assistance strength; if the indicators show excessive assistance (such as excessive tidal volume or inhibition of spontaneous breathing), the assistance pressure proportional factor is lowered to retain the user's spontaneous breathing ability, ensuring that the assistance pressure always meets the user's real-time needs, avoiding the risk of insufficient or excessive assistance, and thus achieving accurate, safe, and efficient respiratory assistance support.

[0058] In the above, refer to Figure 1 The respiratory assistance control method according to the embodiment of the present invention is described in detail. Figure 2 A respiratory assistance control system according to an embodiment of the present invention is described.

[0059] The respiratory assistance control system according to the embodiment of the present invention is used to solve the technical problem that the parameters of the respiratory assistance equipment in the prior art are fixed and cannot accurately adapt to the individual's physiological state, resulting in insufficient accuracy and effectiveness of respiratory assistance control, thereby achieving the technical effect of realizing accurate respiratory assistance control and improving the safety and effectiveness of respiratory assistance control. Figure 2 As shown, the respiratory assistance control system includes: a target chest position acquisition unit 10, a target echo signal acquisition unit 20, a target respiratory signal acquisition unit 30, an auxiliary control optimization analysis unit 40, and a respiratory assistance control unit 50.

[0060] The target chest position acquisition unit 10 is used to activate a predetermined locator to dynamically monitor and obtain the target chest position of the target user; the target echo signal acquisition unit 20 is used to transmit electromagnetic waves based on the target chest position and obtain the target echo signal of the target user; the target breathing signal acquisition unit 30 is used to introduce a predetermined filter to filter the target echo signal to obtain a target breathing signal; the auxiliary control optimization analysis unit 40 is used to dynamically monitor and obtain the target diaphragm electrical activity signal of the target user, and perform auxiliary control optimization analysis in conjunction with the target breathing signal to obtain the optimal auxiliary pressure proportional factor; the breathing assistance control unit 50 is used to perform breathing assistance control on the target user according to the optimal auxiliary pressure proportional factor.

[0061] The specific configuration of the target chest position obtaining unit 10 will be described in detail below. The target chest position obtaining unit 10 further includes: monitoring the target user via the optical camera positioning component in the predetermined positioner to obtain a target optical image; reading predetermined joint positions and annotating the predetermined joint positions in the pre-processed target optical image to obtain a target annotated image; and analyzing the target annotated image to determine the target chest position; wherein the predetermined joint positions include at least the shoulder position, the chest position, and the waist position.

[0062] The specific configuration of the target chest position obtaining unit 10 will be described in detail below. The target chest position obtaining unit 10 further includes: obtaining target infrared radiation of the target user via a thermal imaging positioning component in the predetermined positioner; rendering a target thermal image based on a target electrical signal obtained by converting the target infrared radiation; and analyzing the target thermal image to determine the target chest position.

[0063] The following will further describe in detail the specific configuration of the target chest position obtaining unit 10. The target chest position obtaining unit 10 further includes: the predetermined locator dynamically monitors the target user based on a predetermined frequency.

[0064] The specific configuration of the target respiratory signal acquisition unit 30 will be described in detail below. The target respiratory signal acquisition unit 30 further includes: extracting a passband threshold stored in the predetermined filter; performing preliminary screening processing on the target echo signal using the passband threshold as a screening constraint to obtain an initial respiratory signal; performing modal decomposition on the initial respiratory signal to obtain a signal decomposition result, wherein the signal decomposition result includes a first modal component; comparing the first modal component with the initial respiratory signal to obtain a first value index; and adding the first modal component to the target respiratory signal when the first value index reaches a predetermined value index threshold.

[0065] The following will further describe the specific configuration of the target breathing signal obtaining unit 30. The target breathing signal obtaining unit 30 further includes: obtaining a first feature value of the first modal component; and taking the ratio of the first feature value to the total feature value of the initial breathing signal as the first value index.

[0066] The specific configuration of the auxiliary control optimization analysis unit 40 will be described in detail below. The auxiliary control optimization analysis unit 40 further includes: determining the target breathing index of the target user; using the target diaphragm electrical activity signal and the target breathing signal as simulation constraints, performing simulation analysis on the first auxiliary pressure proportional factor of the target user to obtain first simulation information; reading a predetermined breathing index, and traversing the first simulation information to obtain a first simulation breathing index; when the first simulation breathing index reaches the target breathing index, adding the first auxiliary pressure proportional factor to a candidate list; taking the auxiliary pressure proportional factor corresponding to the maximum index in the candidate list as the optimal auxiliary pressure proportional factor.

[0067] The specific configuration of the auxiliary control optimization analysis unit 40 will be described in detail below. The auxiliary control optimization analysis unit 40 further includes: collecting multi-dimensional user feature parameters of the target user to form a target feature set; performing a weighted calculation on the target feature set to obtain a target individual coefficient; and adaptively adjusting the baseline breathing index based on the target individual coefficient to obtain the target breathing index.

[0068] The respiratory assistance control system provided by the embodiment of the present invention can execute the respiratory assistance control method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0069] Figure 3 1 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing an embodiment of the present invention. Figure 3 The electronic device shown is merely an example and should not limit the functionality and scope of use of the embodiments of the present invention. The electronic device is in the form of a general-purpose computing device, and its components may include, but are not limited to, an input device 401, a processor 402, a memory 403, and an output device 404. The processor 402 may be one or more; the memory 403 may include a computer-readable medium and at least one program product, which has a set (at least one) of program modules configured to perform the functions of the various embodiments of the present application.

[0070] The memory 403 shown in the embodiment of the present invention can adopt any combination of one or more computer-readable media; the computer-readable storage medium can be but not limited to infrared, semiconductor systems, devices or components, or any combination of the above, for storing software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the respiratory assistance control method in the embodiment of the present invention. The processor 402 executes various functional applications and data processing of the computer device by running the software programs, instructions and modules stored in the memory 403, thereby realizing the above-mentioned respiratory assistance control method.

[0071] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0072] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A breathing assistance control method, characterized in that: include: Activate a predetermined locator for dynamic monitoring to obtain a target chest position of a target user; Emitting electromagnetic waves based on the target chest position and acquiring a target echo signal of the target user; introducing a predetermined filter to filter the target echo signal to obtain a target breathing signal; Dynamically monitoring the target diaphragm electrical activity signal of the target user, and performing auxiliary control optimization analysis in conjunction with the target breathing signal to obtain the optimal auxiliary pressure proportional factor; The target user is assisted in breathing control according to the optimal auxiliary pressure proportional factor.

2. The respiratory assistance control method according to claim 1, wherein: Activate the predetermined locator to dynamically monitor and obtain the target chest position of the target user, including: The target user is monitored by the optical camera positioning component in the predetermined locator to obtain a target optical image; Reading a predetermined joint position and marking the predetermined joint position in the preprocessed target optical image to obtain a target marked image; Analyzing the target annotated image to determine the target chest position; Wherein, the predetermined joint positions include at least a shoulder position, a chest position and a waist position.

3. The respiratory assistance control method according to claim 1, wherein: Activate the predetermined locator to dynamically monitor and obtain the target chest position of the target user, including: Acquiring target infrared radiation of the target user through a thermal imaging positioning component in the predetermined locator; Drawing a target thermal image based on a target electrical signal obtained by converting the target infrared radiation; The target thermal image is analyzed to determine the target chest position.

4. The respiratory assistance control method according to claim 2 or 3, characterized in that: The predetermined locator dynamically monitors the target user based on a predetermined frequency.

5. The respiratory assistance control method according to claim 1, wherein: Introducing a predetermined filter to filter the target echo signal to obtain a target breathing signal, including: Extracting the passband threshold stored in the memory of the predetermined filter; Using the passband threshold as a screening constraint, performing preliminary screening processing on the target echo signal to obtain an initial respiratory signal; Performing modal decomposition on the initial respiratory signal to obtain a signal decomposition result, wherein the signal decomposition result includes a first modal component; Comparing the first modal component with the initial breathing signal to obtain a first value index; When the first value index reaches a predetermined value index threshold, the first modal component is added to the target breathing signal.

6. The respiratory assistance control method according to claim 5, characterized in that: Comparing the first modal component with the initial breathing signal to obtain a first value index includes: Obtaining a first characteristic value of the first modal component; The ratio of the first characteristic quantity to the total characteristic quantity of the initial respiratory signal is taken as the first value index.

7. The respiratory assistance control method according to claim 1, wherein: Dynamic monitoring obtains the target diaphragm electrical activity signal of the target user, and performs auxiliary control optimization analysis in conjunction with the target breathing signal to obtain the optimal auxiliary pressure proportional factor, including: determining a target breathing index of the target user; Using the target diaphragm electrical activity signal and the target respiratory signal as simulation constraints, performing simulation analysis on a first auxiliary pressure proportional factor for the target user to obtain first simulation information; Reading a predetermined breathing index and traversing the first simulation information to obtain a first simulated breathing index; When the first simulated breathing index reaches the target breathing index, adding the first auxiliary pressure proportional factor to a candidate list; The auxiliary pressure proportional factor corresponding to the maximum index in the candidate list is taken as the optimal auxiliary pressure proportional factor.

8. The respiratory assistance control method according to claim 7, characterized in that: Determining a target breathing index of the target user includes: Collecting multi-dimensional user feature parameters of the target user to form a target feature set; Performing weighted calculation on the target feature set to obtain a target individual coefficient; The benchmark breathing index is adaptively adjusted based on the target individual coefficient to obtain the target breathing index.

9. A respiratory assistance control system, characterized in that: The system is used to implement the respiratory assistance control method according to any one of claims 1 to 8, and the system comprises: A target chest position obtaining unit is used to activate a predetermined locator for dynamic monitoring to obtain a target chest position of a target user; a target echo signal acquisition unit, configured to transmit electromagnetic waves based on the target chest position and acquire a target echo signal of the target user; a target breathing signal obtaining unit, configured to introduce a predetermined filter to filter the target echo signal to obtain a target breathing signal; an auxiliary control optimization analysis unit, configured to dynamically monitor and obtain a target diaphragm electrical activity signal of the target user, and perform auxiliary control optimization analysis in conjunction with the target breathing signal to obtain an optimal auxiliary pressure proportional factor; A breathing assistance control unit is used to perform breathing assistance control on the target user according to the optimal assistance pressure proportional factor.

10. An electronic device, characterized in that: The electronic device comprises: a memory for storing executable instructions; The processor is configured to implement the respiratory assistance control method according to any one of claims 1 to 8 when executing the executable instructions stored in the memory.

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