141 results about "Tidal volume" patented technology

The invention discloses a real-time image registration and path planning system in bronchoscope surgical navigation, relates to the technical field of image registration, and is used for solving the problems that in a thoracic and abdominal minimally invasive interventional operation, organ movement and deformation caused by breathing of a patient can cause obvious influence on the registration precision of a navigation system, and the navigation precision is poor. Space registration of preoperative images and an anatomical structure of a patient in an operation often has errors due to mismatching of breathing phase changes; multi-attitude data are fused, the respiration interference degree is comprehensively evaluated through double indexes, the problem that a traditional static deformation field cannot be matched with dynamic respiration is solved through respiratory cycle driving deformation prediction, displacement errors are corrected through tidal volume observation values, and B spline control point weights are reversely optimized through registration residual errors. A deformation field can adapt to breathing amplitude and frequency differences of different patients, online distillation learning is carried out by taking a registration error output by a filter as a teacher signal, and local residual deformation and chronic changes which are difficult to describe by a traditional global model are accurately captured.

The invention relates to the technical field of medical instruments, and particularly discloses a deep sleep maintenance algorithm for self-adaptive pressure regulation of a breathing machine, which comprises the following steps: step 1, a data acquisition and preprocessing module is connected with a pressure sensor and a flow sensor in the breathing machine to acquire a breathing pressure signal and a breathing flow rate signal of a patient in real time; 2, the data collecting and preprocessing module further conducts filtering and smoothing processing on the collected respiratory signals, noise and interference components are removed, and normalization processing is conducted on the respiratory flow rate signals; according to the breathing machine self-adaptive pressure regulation micro-awakening suppression algorithm based on the tidal volume dynamic tracking model, by dynamically tracking the tidal volume, the breathing requirement of a patient can be sensed in real time, and the pressure output of the breathing machine is self-adaptively regulated according to the change of the tidal volume; by means of the precise pressure adjusting mode, dyspnea caused by insufficient or too high pressure can be effectively avoided.

The invention discloses a breathing machine output gas monitoring method, system and device and a storage medium. The breathing machine output gas monitoring method comprises the steps that airway pressure information, gas flow information and oxygen concentration information of breathing pipeline gas are obtained; determining tidal volume, respiratory rate and inspiration and expiration ratio according to the gas flow information; performing air leakage compensation on the tidal volume according to the airway pressure information to obtain a real tidal volume; the airway pressure information, the inspiration and expiration ratio, the real tidal volume, the respiratory rate and the oxygen concentration information are displayed. The breathing machine output gas monitoring comprehensiveness and accuracy are improved, and the breathing machine output gas monitoring method can be widely applied to the technical field of breathing machines.

The invention discloses a method and a system for predicting a machine withdrawal behavior of a medical respirator, and relates to the technical field of artificial intelligence, the method for predicting the machine withdrawal behavior of the medical respirator comprises the following steps: acquiring first respiration data generated in the process that a current patient uses the medical respirator in real time; inputting the first respiration data into a trained neural network model; based on the first breathing data, the neural network model generates second breathing data generated after the current patient uses the medical breathing machine in a first time period in the future; whether machine withdrawal can be carried out currently is predicted in real time based on the second respiration data and the neural network model, intelligent prediction is carried out through the neural network model, automatic machine withdrawal decision support is provided by the neural network model based on multiple key parameters such as the respiration frequency, the tidal volume, the oxygenation index and the lung compliance index, the burden of manual judgment is reduced, and the working efficiency is improved. The prediction accuracy and efficiency are improved, and the risk of machine withdrawal failure is reduced.

The invention relates to a functional residual gas amount measuring method and device, equipment and a storage medium. The method comprises the following steps: recording lung electrical impedance change values of a user under a plurality of tidal volumes based on an electrical impedance imaging device to obtain a plurality of tidal volume-lung electrical impedance change value pairs; generating a lung electrical impedance change curve based on the plurality of tidal volume-lung electrical impedance change value pairs, and performing fitting processing on the lung electrical impedance change curve to obtain a fitted lung electrical impedance change curve; acquiring a real-time lung electrical impedance distribution value, and calculating a functional residual gas amount corresponding to the real-time lung electrical impedance distribution value based on the fitted lung electrical impedance change curve; compared with the prior art, the technical scheme of the invention can improve the efficiency and applicability of functional residual gas measurement, so that the method is more suitable for clinical and practical application scenes.

The invention relates to the technical field of medical data mining, in particular to a postoperative pulmonary infection prediction method and system.The postoperative pulmonary infection prediction method comprises the following steps that a continuous data set is formed by collecting breathing parameters and conducting alignment completion, tidal volume and blood oxygen response delay characteristics are extracted through sliding analysis, and a functional abnormal pulmonary segment is located through local anomaly recognition; and fusing physiological and anatomical features to establish a spatial probability map, extracting a respiratory variation coefficient and a risk feature regression analysis confidence index, and outputting an infection risk early warning list with anatomical positioning. According to the method, data faults are eliminated through timestamp alignment to improve the reliability of time sequence association, the breathing compensation capability is quantified through multi-scale window analysis dynamic coupling, lesion avoidance feature masking is accurately positioned through local anomaly detection, and the result interpretability is enhanced through combination of multi-modal feature fusion and space mapping. The three-stage progressive mechanism improves the prediction precision and timeliness, and provides a decision basis with both time sensitivity and anatomical orientation for clinic.

The invention relates to the technical field of rehabilitation assistance, in particular to an intelligent breathing assistance system for lung rehabilitation, comprising: a breathing part, the breathing part comprising a breathing cylinder, the breathing cylinder comprising a fixed cylinder and a folding cylinder, the fixed cylinder being internally provided with an auxiliary assembly; the wearing part comprises a chest cover and an abdomen cover, a connecting channel and a vibration channel are formed in the chest cover, an air bag is embedded in the abdomen cover, and a vibration phlegm eliminating assembly is arranged in the vibration channel; the thoracico-abdominal movement mode recognition unit is used for detecting a breathing mode of a user; the lung function detection unit is used for calculating and detecting the tidal volume of a user; the personalized training control unit is used for adjusting breathing resistance according to the tidal volume and breathing modes, according to different breathing modes of users, the breathing assisting force is adjusted through kinetic energy of gas exhaled by the users, key parameters such as the tidal volume and the recovery condition are monitored in real time, the lung rehabilitation effect is further improved, and the lung rehabilitation effect is improved. And more accurate and effective breathing adjuvant therapy is realized.

The invention relates to the field of surgical monitoring, in particular to a monitoring data analysis system for a surgical operation. The system firstly obtains the inspiration flow velocity and tidal volume at the current moment and each historical moment, analyzes the difference between the inspiration flow velocity at each moment and the inspiration flow velocity at each previous moment, obtains the difference degree of the inspiration flow velocity at each moment, and clusters all moments to obtain the difference degree of the inspiration flow velocity at each moment. According to the difference between the tidal volume of the current moment and the historical moment in the cluster where the current moment is located, the tidal volume difference degree of the current moment is obtained, and according to the difference between the inspiration flow speed and the historical moment and the difference between the tidal volume and the difference between the inspiration flow speed and the historical moment, the difference between the inspiration flow speed and the historical moment is obtained; according to the inspiration flow rate, the tidal volume difference degree at the current moment, the stability similarity at the current moment is obtained, and the anesthesia state of the patient is evaluated according to the inspiration flow rate, the tidal volume and the stability similarity at the current moment. The anesthesia state of the patient can be accurately evaluated, and the accuracy of anesthesia monitoring of the patient is improved.

The invention discloses a federated learning-based air pressure control method for a predictive drive type household respirator, which relates to the technical field of household sleep respirators and comprises the following steps of: training a double-layer long-short-term memory network model by using a self-adaptive moment estimation optimizer to obtain a tidal volume prediction model; aggregation optimization is carried out on the tidal volume prediction models of the breathing machine ends through federal learning, and an optimized global tidal volume prediction model is obtained; the physiological data collected by the respirator end in real time are predicted, and the tidal volume of the patient is obtained; the air pressure output of the breathing machine is adjusted based on the tidal volume. Through cooperative work of the cloud end and the breathing machine end, the neural network model is optimized by using the federated learning algorithm, on the premise of ensuring data privacy, the prediction precision and control performance of the breathing machine are continuously improved, the model used in the breathing machine can be ensured to be more accurately matched with breathing events of different groups, and the breathing efficiency is improved. And the prediction precision and the control effect are improved.

The invention relates to the field of medical instruments, in particular to a respiratory capacity real-time monitoring method and system of a medical vaporizer. According to the method, the initial atomization airflow flow of the medical atomizer is obtained, the breathing signals of the user in the multiple breathing cycles are collected in the first preset time period, and the initial tidal volume information is obtained. Then, the respiratory signals are converted into a power spectrum density map through fast Fourier transform, inspiration waveforms are extracted to obtain tidal volume characteristic values, and deep analysis of the respiratory signals is achieved. Meanwhile, resistance values and temperature values of the heating wire in a plurality of respiratory cycles are collected, a temperature-resistance change coefficient is generated according to the data, and equipment performance changes are quantified. Based on this, the actual atomized airflow flow is calculated in combination with the initial atomized airflow flow and the coefficient. Finally, the actual atomization airflow flow, the tidal volume characteristic value and the coefficient are synthesized to obtain the actual tidal volume, the medicine dosage is matched according to the actual tidal volume, all the steps are linked with one another, and accurate treatment is achieved through multi-dimensional data integration.

The invention discloses an underground breathing flow monitoring method and system based on adaptive filtering, and the method comprises the steps: collecting an airflow signal at the mouth and nose of a miner in real time through an MEMS hot film sensor, and synchronously collecting a body vibration signal through an acceleration sensor, and obtaining original breathing data containing dynamic interference and corresponding vibration data; the method comprises the following steps: preprocessing original breathing data containing dynamic interference and corresponding vibration data to obtain a digital breathing flow signal and a standardized reference vibration signal; jointly inputting the digital respiratory flow signal and the standardized reference vibration signal into a filtering processing model based on an LMS adaptive algorithm to obtain a target respiratory flow signal; performing data analysis on the target respiratory flow signal, and calculating to obtain a real-time respiratory flow value, respiratory frequency and tidal volume parameters of the monitored object; the real-time breathing flow value, the breathing frequency and the tidal volume parameters obtained through calculation are locally displayed in real time, and monitoring of breathing flow data during underground operation is achieved.

The invention provides a small animal breathing machine and a control method, the small animal breathing machine comprises an air pump set, a breathing control valve, a breathing machine controller and a touch screen displayer, the air pump set comprises a plurality of air pump units arranged in parallel and a silica gel pipeline, the multiple air pump units are connected in parallel, and the air pump units with different flows can be freely combined according to different animal and tidal volume requirements; the air flow of each air pump unit is accurately distributed, meanwhile, the high-precision and large-flow requirements of the breathing machine are met, a three-way pipeline and a valve element are arranged in the breathing control valve, and the pulmonary alveolar connecting end, the three-way pipeline and the air outlet pipeline form an air inlet path; the alveolar connecting end, the three-way pipeline and the waste collecting end form an exhaust gas path, and the valve element can switch the direction of an internal gas path of the three-way pipeline. The breathing control valve controls the airflow direction only through the action of the valve element, so that the air pump unit can operate continuously, frequent starting and stopping are not needed, the service life of the air pump unit is remarkably prolonged, and the response speed is increased.

The invention relates to a working parameter adjusting method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring gas pressure and gas flow rate output by a breathing machine and collected by a breathing machine sensor; determining breathing information of the target user according to the gas pressure and the gas flow rate; the breathing information comprises at least one of breathing frequency, real-time tidal volume and breathing quality data; determining physiological state information of the target user according to the breathing information and a physiological state threshold value; and adjusting working parameters of the breathing machine based on the physiological state information. By analyzing the gas pressure and flow velocity data collected by the respirator sensor in real time, the breathing frequency, tidal volume and other key parameters of a user can be accurately determined, the breathing state of a patient is intelligently evaluated, the working parameters of the respirator are automatically adjusted according to the evaluation result, and the flexibility of the working parameters is improved.

The invention provides a lung expiration training system for nursing a patient outside a chest, which relates to the technical field of medical rehabilitation training and comprises a respiratory signal acquisition module, a main control and signal processing module, a feedback and excitation module and a data management and scheme customization module, the respiratory signal acquisition module is used for acquiring an instantaneous pressure difference signal in the expiration process of a patient in real time by utilizing a differential pressure type flow sensor; the main control and signal processing module converts the pressure difference signal into instantaneous flow, obtains an expiration flow-time curve, a primary expiration amount and expiration efficiency based on discrete sampling, smooth operation and integral calculation, and calculates an error sum of squares and a curve goodness of fit to form a comprehensive control amount; the feedback and excitation module provides visual, auditory or tactile feedback according to the comprehensive control quantity, and can present a gamification interface to guide the patient to adjust the breathing rhythm; the data management and scheme customization module is used for setting a personalized training scheme and recording training data, and the trend analysis unit generates a rehabilitation trend report based on historical indexes.

The invention belongs to the technical field of biological medicine, and particularly relates to application of corynebacterium casei in preparation of medicine for preventing and treating lung injury. By constructing a radon inhalation-induced lung injury mouse model, after exposure at different radon levels, the weight of a mouse is reduced, the lung coefficient is increased, the tidal volume of the lung, the ventilation volume per minute and the maximum inspiration flow are reduced, the respiratory function is inhibited, the alveolar cavity of the mouse is abnormally expanded, the pulmonary septum is thickened and fractured, and more fibrin exudation is accompanied; the traditional Chinese medicine composition can be used for effectively inhibiting pulmonary fibrosis and lung injury due to obvious inflammatory infiltration beside bronchial tubes, extravasated blood in small blood vessels and lung tissue collagen deposition, and can be used for gavage of corynebacterium casei to effectively inhibit the above phenomena. Therefore, the corynebacterium casei can be used for preventing and treating lung injury, especially lung injury caused by radon exposure.

The invention discloses an intelligent processing method and system for physiological data of a respiratory critically ill patient, and the method comprises the steps: carrying out the STL time sequence decomposition of a volume-time curve, obtaining the residual terms of the volume-time curve under abnormal fluctuation and no abnormal fluctuation, and judging whether the current volume data is abnormal data or not; obtaining the possibility of abnormal tidal volume caused by airway leakage based on the residual value representation of the respiratory cycle corresponding to the obtained abnormal data on the airway pressure-time curve; and based on the possibility of the abnormal data and the possibility of the abnormal tidal volume caused by the airway leakage, obtaining the abnormal degree of the abnormal tidal volume data caused by the airway leakage, and correcting the abnormal data according to the abnormal degree of the abnormal tidal volume data caused by the airway leakage. According to the invention, the possibility of abnormal data can be accurately judged, and intelligent correction can be carried out according to the abnormal degree, so that tidal volume data closer to reality can be obtained.

The invention provides an airway atomization flow intelligent drug delivery control method and system, and relates to the technical field of medical instruments.The method comprises the steps that basic information of the age, the weight and the illness state severity of a patient is obtained, and physiological parameters of the respiratory rate and the tidal volume of the patient are collected in real time through a sensor; inputting the basic information and the physiological parameters into a fuzzy adaptive control algorithm, and initializing an individual administration rule base according to the basic information; based on the real-time change trend of the respiratory rate and the tidal volume, three initial control index values including an atomization flow value, a drug concentration value and a time interval are dynamically generated through a membership function. According to the invention, through the full-process design of data acquisition, intelligent modeling, accurate execution and data closed loop, intelligentization of atomization treatment is realized.

The invention relates to the field of intelligent medical treatment, in particular to a numerical model for predicting deposition distribution of heterogeneous particles in animal respiratory tracts and a construction method of the numerical model. Comprising the following steps: acquiring image data, particle attributes, fluid flow state types and respiratory tidal volume of animal respiratory tracts; performing three-dimensional reconstruction on the respiratory tract area through the image data to obtain a respiratory tract model; analyzing particle stress through fluid flow state types and particle attributes to construct a particle motion tracking model; calculating the respiratory tract deformation quantity of the respiratory tract model through the respiratory tidal volume to construct a respiratory tract deformation model; and combining the respiratory tract model, the particle motion tracking model and the respiratory tract deformation model to obtain the animal respiratory tract heterogeneous particle deposition distribution numerical model. The device can simulate deposition distribution and deposition amount of heterogeneous particles in different areas of the respiratory tract, and has good application value.

The invention relates to a breathing machine, a pressure and tidal volume adjusting method, device and equipment thereof and a medium, and the method comprises the steps that the carbon dioxide concentration of the expiration tail end of a patient is obtained; determining a pressure compensation value of the breathing machine according to the carbon dioxide concentration and a preset carbon dioxide concentration threshold value; real-time pressure of the breathing machine is obtained, and a target pressure value is obtained based on the pressure compensation value and the real-time pressure; calculating a target tidal volume according to the target pressure value; and adjusting the pressure and tidal volume of the breathing machine based on the target pressure value and the target tidal volume. In the whole process, the pressure and the tidal volume of the breathing machine are compensated / adjusted based on the carbon dioxide concentration of the exhalation tail end of the patient, the breathing machine can continuously and stably provide appropriate pressure and tidal volume support according to the actual exhalation carbon dioxide concentration of the patient, and stable adjustment of the pressure and the tidal volume of the breathing machine is achieved.

The invention relates to a parameter adjusting method and device of a breathing machine, computer equipment and a storage medium. The method comprises the following steps: acquiring gas state data and environment state data of the breathing machine; according to the gas state data and the environment state data, target adjusting parameters of the breathing machine are determined; the target adjusting parameters comprise at least one of target tidal volume, target breathing flow, breathing pressure rise time, target water tank temperature and target water tank humidity; and according to the target adjustment parameter, performing parameter adjustment on the breathing machine. Closed-loop feedback control of the gas state data and the environment state data is synchronously achieved, and the target tidal volume, the target breathing flow, the breathing pressure rising time, the target water tank temperature and the target water tank humidity are cooperatively adjusted, so that the systematic precision and the dynamic response efficiency of parameter regulation and control of the breathing machine are remarkably improved.

The invention discloses an electric turbine anaesthesia machine with an automatic air supply function of an air storage bag and a method, and the anaesthesia machine comprises a turbine which is used as an active inspiration air source; a detachable air storage bag; an air supply one-way valve; the breathing circuit is connected between the turbine outlet and the patient end and comprises an inspiration branch provided with a flow diaphragm, an expiration branch provided with an expiration EV valve and an expiration flow diaphragm, and a patient breathing circuit tank assembly containing the air storage bag and the soda lime tank; a plurality of sensors; the control unit is electrically connected with and controls the turbine and the expiration EV valve, receives signals of the sensor and is used for achieving different breathing ventilation modes. According to the anesthesia machine and method, turbine driving is adopted, the tidal volume adjusting range is wide, and physical limitation of a folding bag is avoided; the air storage bag is externally arranged and replaceable, so that cleaning and maintenance are facilitated; a one-way valve automatic gas supply mechanism ensures continuous and stable gas supply; the device supports various breathing modes, and is suitable for various scenes such as anesthesia maintenance, postoperative awakening, oxygen therapy and the like.

The utility model belongs to the technical field of medical first-aid equipment, and discloses a full-automatic breathing balloon pressing device which comprises a breathing balloon body and a support, the breathing balloon body comprises a balloon, one end of the balloon is connected with a connecting pipe communicated with an inner cavity of the balloon, and the inner wall of the connecting pipe is connected with a pressure sensor and a flow meter respectively. According to the scheme, manual operation is replaced with the automatic pressing structure, and the problems that a traditional breathing balloon is unstable in pressing frequency, uneven in force, fatigue and the like are solved; a pressure sensor and a flow meter are combined to realize real-time monitoring and intelligent regulation and control, so that the ventilation pressure and the tidal volume are effectively controlled, and the safety is improved; the adjustable fixing assembly adapts to various balloon sizes, and stable pressing is ensured; the common and advanced modes adapt to different treatment requirements and are widely applied to pre-hospital first aid and intensive care, and the respiratory support efficiency and reliability are remarkably improved.

The present invention belongs to the field of biomedicine technology, and in particular to the application of Corynebacterium casei in the preparation of medicines for preventing and treating lung injury. The present invention constructs a mouse model of lung injury caused by radon inhalation and finds that after exposure to different radon levels, the mice lose weight, increase the lung coefficient, reduce the lung tidal volume, minute ventilation and maximum inspiratory flow, and their respiratory function is inhibited. The alveolar cavity of the mice is abnormally expanded, the lung septum is thickened and fractured, accompanied by more fibrin exudation, obvious inflammatory infiltration appears near the bronchus, congestion occurs in small blood vessels, and collagen deposition in lung tissue can lead to the occurrence of pulmonary fibrosis, causing lung injury. Oral administration of Corynebacterium casei can effectively inhibit the above-mentioned phenomenon. Therefore, Corynebacterium casei can be used for the prevention and treatment of lung injury, especially lung injury caused by radon exposure.

The embodiment of the invention relates to the technical field of sleep-aiding sound turn-off, and discloses a sleep-aiding sound turn-off method, a breathing machine and a controller. The method comprises the steps of obtaining a target respiratory rate, a target tidal volume, a target respiratory rate reference value and a target tidal volume reference value, comparing the target respiratory rate with the target respiratory rate reference value to obtain a first result, and comparing the target tidal volume with the target tidal volume reference value to obtain a second result, judging that the user enters a sleep state according to the first result and the second result, determining that the user enters the sleep state, and stopping playing the sleep-aiding sound. According to the embodiment of the invention, the target respiratory rate, the target tidal volume, the target respiratory rate reference value and the target tidal volume reference value can be acquired and compared and analyzed, so that the sleep-aiding sound can be closed after the user enters the sleep state, a more intelligent solution for closing the sleep-aiding sound is provided for the user, and the user experience is improved. The user can enter the sleep state more comfortably, and the overall sleep experience is improved.

This invention provides a non-contact method, device, equipment, and storage medium for measuring trunk respiratory parameters. It synchronously acquires three-dimensional motion data of optical reflective markers during respiration, with these markers positioned at multiple pre-defined anatomical landmark locations on the subject's trunk. Based on the three-dimensional motion data, it determines the volume change of the spatial envelope formed by the optical reflective markers. According to a pre-established mapping relationship between the volume change and tidal volume, it converts the volume change into tidal volume. Based on the signal of the volume change over time, it extracts the respiratory rate. Finally, it calculates the total respiratory volume based on the tidal volume and the respiratory rate. By combining optical motion capture with spatial geometric modeling, it achieves non-contact, continuous, and high-precision measurement of trunk respiratory motion, effectively overcoming the shortcomings of traditional methods, such as reliance on patient cooperation, invasiveness, expensive equipment, and complex operation.

A stand-alone, fully integrated self-contained wearable metabolic analyzer for metabolic rate and respiratory quotient measurement. It includes a device body, disposable mask, and headgear. The device body comprises multiple different miniaturized modules, including a colorimetric sensing module, flow module, control circuit, power module, environmental sensors, wireless module, communication module, memory module, signal processing module, and display module. A disposable sensor chip, coated with chemical sensing probes, is utilized in the colorimetric sensing module for breath O2 and CO2 detection. A Venturi tube and pressure sensor-based flow module measures breath flow rate. The self-contained wearable metabolic analyzer derives physiological parameters including resting energy expenditure (REE), respiratory quotient (RQ), oxygen consumption (VO2), carbon dioxide production (VCO2), minute ventilation (VE), breath frequency (BF), and tidal volume (TV) from the measurement.

The invention relates to the technical field of medical equipment, and discloses an external oxygen supply method, an external-oxygen-free oxygen supply method and a quantitative oxygen supply method, and provides three core modes: in an external oxygen supply mode, redundant oxygen during extrusion is recycled and reused through a gas storage bag, and overpressure is prevented in combination with a pressure release valve; in the oxygen supply mode without external oxygen, pure manual extrusion air supply is achieved through a shell which can be replaced or arranged outside the air bag in a sleeving mode, and the device adapts to the oxygen-source-free environment; in the quantitative oxygen supply mode, the inflatable inner bag is arranged in the air bag to accurately limit the oxygen storage space in advance, and accurate control over the single tidal volume is achieved. According to the invention, the oxygen utilization rate is obviously improved, the use safety is guaranteed, and the application capability of the simple respirator in precise ventilation and emergency scenes is expanded.

The invention relates to a breathing machine and an oxygen mixing control method and device thereof, computer equipment and a medium, and the method comprises the steps that external input oxygen is controlled to enter an oxygen mixing negative pressure cavity, and the oxygen flow entering the oxygen mixing negative pressure cavity is calculated; acquiring automatic inspiration pressure and tidal volume of the respirator; according to the automatic inspiration pressure, the tidal volume and the oxygen flow, a pressure compensation value of inspiration pressure change caused by oxygen mixing is calculated; and performing compensation control on the output pressure of the breathing machine according to the pressure compensation value. In the whole scheme, on one hand, mixing of externally input oxygen is achieved through the negative pressure cavity, and oxygen mixing is more sufficient; on the other hand, the influence of the negative pressure cavity on the output pressure of the breathing machine during oxygen mixing is considered, a corresponding pressure compensation value is calculated based on the automatic inspiration pressure, the tidal volume and the oxygen flow, then compensation control is conducted on the output pressure of the breathing machine, and it is ensured that the output pressure of the breathing machine is stable.

This invention belongs to the field of particulate matter toxicity assessment for environmental health, and discloses a health risk assessment method based on the respiratory tract deposition rate of particulate matter of different sizes and its application. The method collects the concentrations of toxic benzene series compounds and naphthalene in human exhaled breath and atmospheric particulate matter of different sizes in the environment; detects human tidal volume and respiratory rate to obtain minute ventilation. Then, using the ICRP model combined with Python software to process the data, the respiratory tract deposition fractions of benzene series compounds and naphthalene in different regions of the human respiratory tract are obtained. Finally, the respiratory tract deposition amount is obtained based on the respiratory tract deposition amount formula, and the deposition rate of benzene series compounds and naphthalene in the human respiratory tract is obtained by dividing the respiratory tract deposition amount by time. This method is simple, fast, and highly accurate, effectively exploring the deposition rate of toxic components in different particle sizes of particulate matter in the main parts of the human respiratory tract and corresponding health risk assessment, which is of great significance for health exposure to environmental pollutants.

The invention discloses a plateau altitude self-adaptive compensation system and method for an emergency breathing machine. The plateau altitude self-adaptive compensation system comprises a sensing module, a control module, a power module, a gas circuit driving circuit, a man-machine interaction module, an execution module and an additional function module. Acquiring a plateau altitude self-adaptive compensation data set; the plateau altitude adaptive compensation data set comprises altitude height information, fan parameter information, atmospheric pressure information, airway pressure information, gas flow information and temperature information; training a preset fan drive control model by using the plateau altitude self-adaptive compensation data set to obtain an optimized fan drive control model; and processing plateau altitude self-adaptive compensation data to be processed by utilizing the optimized fan drive control model to realize plateau altitude self-adaptive compensation of the emergency breathing machine. The method can adapt to different altitudes and automatically compensate the influence of atmospheric pressure change on tidal volume and minute ventilation output precision.