363 results about "Respiratory cycle" 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 discloses a virtual dynamic three-dimensional image fusion method and system based on pre-registration, and the method comprises the steps: obtaining a static three-dimensional image of a target region, and a dynamic three-dimensional CBCT image which at least comprises one respiratory cycle; performing breathing phase division on the dynamic three-dimensional CBCT image; obtaining a corresponding three-dimensional image frame on each phase node; registering the plurality of three-dimensional image frames obtained by division with the static three-dimensional image in sequence to obtain a single-frame deformation field; collecting breathing signals of a patient in real time during an operation; performing interpolation calculation on the single-frame deformation field based on the respiratory signal, and generating a complete deformation field in the whole respiratory cycle in real time; and applying the complete deformation field obtained by interpolation to the static three-dimensional image, so that the static three-dimensional image is virtually dynamic. Through a method of pre-registration of a pre-operative breathing phase node image and interpolation based on a real-time breathing phase in an operation, the calculation amount during real-time fusion in the operation is reduced, so that ultra-low-delay image fusion is realized.

Disclosed herein are systems, devices, and methods for stimulating nerves, including electrically stimulating peripheral nerve(s) to treat various diseases and disorders, as well as systems and methods for applying stimulation waveforms for improving the therapeutic benefit, outcomes, and / or experience relating to the same. Some systems and methods generate a biphasic stimulation waveform that includes a plurality of pulses with alternating leading phases. Some systems and methods vary one or more parameters of the stimulation waveform to correlate with a characteristic of the user. Example characteristic of the user include a phase of a tremor exhibited by the user and a respiratory cycle of the user. For some systems and methods, the stimulation waveform includes a plurality of burst with each burst ramping up in amplitude. For some systems and methods, the stimulation waveform is delivered during a time period that includes an on-cycle portion and an off-cycle portion with the stimulation waveform only being delivered during the on-cycle portion of the time period.

The invention discloses a multi-source data-based medical temperature-adjusting atomization drug delivery system for the pneumology department, relates to the technical field of medical temperature-adjusting atomization drug delivery, and aims to solve the problems that the atomization effect is poor and the atomization process is not intelligent. By adjusting atomization power in different respiratory cycle stages, monitoring airway abnormity and respiratory fluctuation in real time to correct parameters and adapting temperature control and atomization components as required, medicine waste and airway stimulation can be reduced, variables such as air source fluctuation and liquid medicine viscosity can be coped, atomization stability is guaranteed, administration efficiency and safety are improved, and the method is suitable for large-scale popularization and application. The requirements of patients with weak respiratory functions are met, the basic information unit is linked with the medical history of the patients and the medicine information to determine the safe temperature, the atomization rhythm is matched in combination with the respiratory parameters, temperature deviation caused by information dispersion can be avoided, manual errors are reduced, and the medication safety is improved.

The invention discloses a non-contact temperature calibration method and system, electronic equipment and a storage medium, and relates to the technical field of temperature calibration. The method comprises the following steps: acquiring a surface temperature value of a bionic head mold; collecting a temperature measurement value of the standard temperature source by the thermometer to be calibrated and an environment parameter value of the environment, wherein the environment parameter value comprises a temperature fluctuation value and a humidity fluctuation value; performing segmentation processing on the environment parameter values and the temperature measurement values based on a preset human body breathing frequency to obtain an environment parameter value sequence and a temperature measurement value sequence corresponding to a plurality of breathing cycles; calculating the fluctuation gradient corresponding to the environmental parameter value sequence in each respiratory cycle and the deviation change rate between the temperature measurement value sequence and the surface temperature value; and determining a temperature compensation coefficient according to the fluctuation gradient and the deviation change rate, and calibrating the temperature measurement value of the to-be-calibrated thermometer based on the temperature compensation coefficient to obtain a target temperature value. By implementing the technical scheme provided by the invention, the effect of improving the accuracy of temperature measurement is achieved.

The invention relates to the technical field of emotional robots, and discloses an embracing emotional robot which comprises an inner shell, low-cost and high-simulation breathing simulation is achieved through cooperative control of an air pump and an air valve, and the embracing emotional robot is designed by combining simulation body temperature brought by a heating piece and synchronous action of a rotatable arm. The emotion robot can naturally rotate forwards when being embraced and is matched with simulated respiration and simulated body temperature, so that the immersion and emotion interaction experience of a user are remarkably improved; the operation cycle of the air pump strictly follows biological breathing characteristics, the inspiration stage accounts for 2 / 3 of the breathing cycle, the speed of the inspiration stage changes fast and slow, the expiration stage accounts for 1 / 3 of the expiration stage, smooth pressure relief is achieved through the air valve, and the highly-simulated breathing mode can effectively guide a user to breathe synchronously, so that parasympathetic nerves are activated, the anxiety level and heart rate fluctuation are reduced, and the user experience is improved. And the whole structure adopts a modular design, complex functions such as breathing simulation, embracing and body temperature simulation can be realized, the maintenance is convenient, and the device is particularly suitable for long-term accompanying scenes.

The invention discloses a PET / MR (positron emission tomography / magnetic resonance) all-in-one machine-based dynamic attenuation correction and respiratory and cardiac dual motion correction method. The method comprises the following steps of: generating a dynamic mu graph of a respiratory cycle; mR cardiac function movie sequence scanning of the cardiac cycle; accurately segmenting the cardiac muscle; 6, performing tissue segmentation on the dynamic mu graph; clustering the PET data; pET data space-time registration is carried out; merging PET data of the same time phase; performing frame-by-frame dynamic attenuation correction; respiratory movement correction; correcting a partial volume effect; carrying out myocardial MR image space standardization on different time phases of the cardiac cycle; and carrying out spatial standardization on the myocardial PET image of different time phases in the cardiac cycle. According to the method, the mu graph of the respiration and cardiac cycles is reconstructed through time-phase sharing and is accurately registered with the PET data, so that the high-quality attenuation correction of the heart PET image is realized and the motion correction is completed at the same time.

The invention discloses a target position prediction method and system based on body surface point cloud data, and relates to the technical field of medical signal processing, and the method comprises the steps: obtaining 4DCT reconstruction point cloud data of a plurality of subjects and body surface point cloud data in a respiratory cycle, and building an in-vivo point cloud data set and a body surface point cloud labeling data set; training a body surface and in-vivo point cloud correlation model by using the body surface point cloud labeling data set and the in-vivo point cloud data set, inputting 4DCT reconstruction point cloud data of the patient and the body surface point cloud contour of the current breathing moment into the trained body surface and in-vivo point cloud correlation model, and obtaining a final prediction phase and a final target region transformation matrix; and in combination with the 4DCT reconstructed point cloud data and the body surface point cloud contour at the current breathing moment, obtaining a predicted position of the in-vivo target region on the body surface point cloud contour at the current breathing moment. According to the invention, the position of the target area can be accurately predicted on the body surface contour, the accuracy of radiotherapy irradiation is improved, and radiation hazards are reduced.

The invention relates to the technical field of atomization rate control, in particular to an intelligent atomization compliance monitoring method and system for children. The method comprises the following steps: firstly, acquiring expiration flow velocity, inspiration flow velocity and multi-direction motion acceleration time sequence data of a child in a historical monitoring period, and reflecting breathing and behavior action conditions; dynamically analyzing the numerical characteristics of the expiration flow velocity and the inspiration flow velocity to divide a respiratory cycle, and analyzing the cycle length, the inspiration flow velocity cumulant and the like to construct a respiratory characteristic vector; screening a target monitoring period based on the breathing feature vector and the period number similarity; further analyzing the motion acceleration change and accumulation characteristics in the target monitoring period, and quantifying the behavior compliance expression degree; the behavior compliance expression degree and the breathing feature vector are deeply fused, a'breathing state-behavior cooperation 'joint evaluation model is established, the breathing and behavior states of children are dynamically recognized, the medicine atomization rate is accurately adjusted, and effective deposition of lung medicine is improved.

The invention discloses a tumor respiratory movement trajectory prediction method and system based on spatio-temporal feature separation LSTM, and the method comprises the following steps: collecting a four-dimensional CT respiratory cycle image, extracting a tumor centroid coordinate, and generating a standardized tumor centroid coordinate sequence through sliding window standardization; the method comprises the following steps: inputting bidirectional LSTM to calculate Euclidean distance screening features and weighting to generate a weighted spatial feature vector sequence, extracting time recursion feature weighted fusion through one-dimensional convolution and unidirectional LSTM, predicting a tumor motion trajectory through autoregression, and comparing real-time coordinate correction to generate an adaptive correction trajectory prediction result. A four-dimensional image sequence is extracted and standardized through registration, a two-way network is combined to calculate two-way distance features to recognize breathing phase changes, spatial-temporal features are fused to establish a nonlinear recursive relation to capture tumor motion differences, real-time correction optimization is achieved through deviation statistics and weight self-adjustment, and prediction stability and trajectory fitting precision are improved.

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

Aspects of the present technology comprise a positioning and stabilising structure to hold a seal-forming structure in a therapeutically effective position on a head of a patient. The seal-forming structure may be constructed and arranged to form a seal with a region of the patient's face surrounding an entrance to the patient's airways for sealed delivery of a flow of air at a therapeutic pressure of at least 4 cmH2O with respect to ambient air pressure throughout the patient's respiratory cycle in use. The positioning and stabilising structure may comprise a front hoop arranged to contact, in use, at least a region of the patient's head superior to an otobasion superior of the patient's head and a rear strap. The positioning and stabilising structure may comprise an adjustment mechanism for adjustment of the front hoop and the rear strap relative to the patient's head, the adjustment mechanism being arranged in a single operation to adjust both the front hoop and rear strap to enable the positioning and stabilising structure to fit different size heads.

The invention relates to the technical field of sleep assessment, and discloses a sleep monitoring method, a breathing parameter control method and breathing equipment, and the method comprises the steps: obtaining an airflow rate signal of a user in a first time period; according to the airflow rate signal of the first time period, the breathing depth and the breathing rate of each breathing cycle are determined; processing the breathing depth and the breathing rate of each breathing cycle, and determining time domain features, frequency domain features and nonlinear features corresponding to the breathing depth and the breathing rate in a plurality of second time periods; based on the trained machine learning model and the time domain features, the frequency domain features and the nonlinear features corresponding to the breathing depths and the breathing rates in the multiple second time periods, the sleep states of the user in all the second time periods are determined, and the sleep states comprise the sober stage, the light sleep stage, the deep sleep stage and the rapid eye movement stage. According to the invention, sleep quality evaluation can be carried out without adding extra hardware and changing the sleep environment, and the accuracy of the determined sleep quality is improved.

The invention discloses an automatic cough identification method for respiratory support equipment, which comprises the following steps of: setting an air leakage threshold, judging whether the air leakage at the current moment is less than the air leakage threshold, if so, executing the next step, otherwise, re-initializing; acquiring flow information of the current task, performing filtering processing to obtain filtering flow of the current task, and calculating a filtering flow difference value between the filtering flow of the current task and the filtering flow of the previous task; the filtering flow difference value and the pressure difference value are judged; if the filtering flow difference value is larger than the pressure difference, 1 is added to the counting value, and the next step is executed; and judging whether the flow waveform has a wave trough, if so, judging whether the counting value is greater than a counting threshold value, and judging whether the absolute value of the current task wave trough value is greater than the average value of the absolute values of the wave trough values of the first N respiratory cycles, and if so, marking the current timestamp as a cough time node. The technical problem that existing respiratory support equipment cannot automatically recognize the cough of a patient and perform early warning is solved.

The invention relates to the technical field of medical image processing, and discloses a tumor state prediction method, system and device and a medium, and the method comprises the steps: obtaining a CT image group of a lung of a target object in a current respiratory cycle, and constructing a three-dimensional tumor model of a lung tumor based on the CT image group; the lung tumor has a real volume and a real centroid coordinate; performing finite element analysis to obtain a finite element tumor model, and calculating the simulated volume and simulated centroid coordinates of the lung tumor; comparing to obtain a volume retention ratio and a gravity center offset; performing motion state prediction on the lung tumor in the next respiratory cycle to obtain an initial motion state parameter of the lung tumor in the next respiratory cycle; if it is judged that the motion state prediction quality of the lung tumor meets the preset motion state prediction quality based on the volume retention ratio and the gravity center offset, the initial motion state parameters serve as the target motion state parameters, the motion state of the lung tumor is obtained through prediction, and the accuracy and accuracy of radiotherapy irradiation are improved.

The invention relates to the technical field of precise monitoring medical treatment, and discloses a breathing machine control strategy debugging method and system based on an EIT image, and the method comprises the steps: constructing a breathing machine control algorithm model based on deep learning through a case library, and representing a mapping relation between a case EIT image and a key index thereof and a breathing machine ventilation control parameter; acquiring current EIT images of a plurality of respiratory cycles of the patient, inputting the current EIT images into the respirator control algorithm model, matching the most similar case from the case library, and performing respirator ventilation control by using target respirator ventilation control parameters of the most similar case; operation is controlled to start, adjustment EIT images and key indexes of a plurality of respiratory cycles of the patient are obtained, and the adjustment EIT images and the key indexes are compared with the EIT images and the key indexes of the most similar cases for judgment; if the requirements are met, continuously controlling and updating the case library, and optimizing the model; otherwise, switching the control mode. Determination of breathing machine control parameters participated by a patient is reduced, trial and error times of clinical parameter adjustment are reduced, and patient safety and control accuracy are both considered.

The invention relates to a dynamic tumor tracking method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring 4DCT image data of a patient, and performing mixed data enhancement on the 4DCT image data to generate a 3DCT image representing each respiratory stage of the lung; based on the 3D CT image, generating an X-ray image in a respiratory cycle of a simulated patient by adopting a mathematical simulation method; registering the X-ray image and the 4DCT image data to generate a tumor tracking model of the patient; and inputting an X-ray image of a patient in a radiotherapy process into the tumor tracking model, and outputting a tumor tracking result through the tumor tracking model. According to the invention, real-time three-dimensional tracking of the tumor can be realized by using a single low-dose X-ray image under any geometric condition, high-precision tumor positioning can be provided on the premise of ensuring low radiation dose, the method is suitable for any projection angle and source-object distance change conditions, and various geometric relationship changes in the treatment process can be flexibly coped with.

An implantable neuromodulation system can include an electrode configured to be disposed at or near a first branch of a hypoglossal nerve of a patient and configured to provide a first electrostimulation therapy to treat a sleep disorder or breathing disorder of a patient. The system can include a sensor configured to provide a sensor signal that includes information about a patient response to the first electrostimulation therapy, information about a patient respiration, or information about one or more other physiologic status indicators for the patient. The sensor signal information can be used to quantify a progression of a breathing disorder for the patient.

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 a cone beam CT full respiratory cycle image reconstruction method based on a four-dimensional neural network. The method comprises the following steps: step 1, acquiring cone beam projection data and a respiratory signal in a respiratory state; 2, a respiratory cycle is divided into N phases, multi-phase cone beam projection data Qi are obtained, i = 1, 2,..., N, the Qi is reconstructed through a filtered back projection algorithm, and a multi-phase under-sampling CT reconstructed image # imgabs0 # is obtained; 3, # imgabs1 # is input into a four-dimensional neural network, and a three-dimensional deformation field Di is obtained; 4, performing weighted summation after deformation on the # imgabs2 # by using the Di to obtain a reference phase reconstruction image Xref after motion correction; and step 5, performing inversion on the Di to obtain a three-dimensional reverse deformation field # imgabs3 #, for any breathing phase, performing image deformation on the reference phase reconstruction image Xref by using the corresponding # imgabs4 #, and performing reconstruction to obtain a motion correction image Xi. According to the method, the breathing movement correction can be quickly carried out on the cone beam CT image.

The invention relates to the technical field of biology, and discloses a mechanical ventilation patient airway management optimization method and system based on artificial intelligence, electronic equipment, a medium and a program product, and the method comprises the steps: assembling a sound collection device, collecting airway sound wave data, and screening and classifying the airway sound wave data according to requirements; processing the reserved airway sound wave data, removing redundant information, and separating the airway sound wave data into single respiratory cycle samples by detecting sound loss between breaths; establishing an ANN classification and identification model of the airway secretions, determining parameter setting of the model, and verifying stability and accuracy of the trained ANN classification and identification model of the airway secretions by using the airway sound wave data; and determining an output result of the ANN classification and identification model of the airway secretions, and judging whether the airway secretions of the patient exist or not according to the output result of the ANN classification and identification model of the airway secretions.

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 relates to the technical field of breath monitoring, in particular to a big data intelligent health breath dynamic monitoring method and system and a terminal. The method comprises the following steps: acquiring a time domain interval of each respiratory cycle according to change characteristics of a respiratory pressure signal; further obtaining work doing amount corresponding to each breathing cycle, and dividing breathing modes; the newest seasonal period of the respiratory pressure signal is further extracted, and a respiratory stability coefficient is obtained according to the change characteristics of work doing amounts of respiratory periods with adjacent time sequences in the seasonal period in combination with the number distribution characteristics of the respiratory periods of the respiratory mode; furthermore, when the breathing stability coefficient is larger than or equal to the preset stability threshold value, the predicted breathing pressure signal is obtained and verified, and finally the predicted breathing mode is obtained according to the final predicted breathing pressure signal, so that the hysteresis of real-time processing is reduced, the response speed of breathing support is increased, and the comfort is improved.

The invention discloses a chest wall defect three-dimensional reconstruction and personalized repair material design system, and relates to the technical field of intelligent medical aided design. Comprising a data acquisition module used for acquiring and preprocessing multi-modal data of the chest wall of a patient; the partition module is used for dividing the defect area into different functional partitions by coupling and analyzing stress and blood flow data and setting a threshold value; the dynamic optimization module is used for mapping the breathing time sequence to a three-dimensional space and dynamically correcting the partition boundary according to the stress change in the breathing cycle; the interface matching module is used for carrying out parameterization design on a host bone interface according to the bone mineral density data; and the optimization design module is used for carrying out topological structure and pore distribution dual optimization on the repair material based on the dynamic partition and the interface parameters, and finally, the output module generates design data capable of directly driving manufacturing. Precise matching of the repairing material and the physiological anatomical structure and the dynamic physiological function of the patient is achieved.

The invention provides a method and equipment for constructing lung function characteristics during sleep. The method is applied to lung function data processing. The method comprises the following steps: collecting a breathing velocity waveform of a target object; determining an inspiration stage and an expiration stage in each respiratory cycle based on the respiratory velocity waveform; the duration of each stage is determined based on the inspiration stage and the expiration stage, and the duration of the inspiration sub-stage and the duration of the expiration sub-stage are obtained; basic features, a stability measurement feature group and a comprehensive feature group are calculated based on the inspiration sub-stage duration and the expiration sub-stage duration; according to the method, the breathing speed waveform is acquired without burden, and the comprehensive lung function evaluation feature group suitable for the radar breathing waveform is constructed.

The invention relates to a ventilation detection device for a myasthenia gravis patient, and the device comprises a muscle strength monitoring module which is configured to monitor the swallowing muscle of the myasthenia gravis patient and the muscle activity of the near end of the limb, and obtains the muscle strength data of the myasthenia gravis patient; the respiration monitoring module is configured to detect the respiration frequency, the tidal volume of each respiration cycle and the inspiration time of each respiration cycle under the condition that mechanical assisted ventilation is carried out on the myasthenia gravis patient, and the change trend along with time is obtained; the control module is in signal connection with the muscle strength monitoring module and the respiration monitoring module, and is configured to control the respiration monitoring module when the muscle strength data of the serious myasthenia patient is lower than a preset muscle strength threshold value and the change trend of the respiration frequency, the tidal volume of each respiration cycle and the inspiration time along with the time is inconsistent with the change trend of pre-stored corresponding parameters; and determining that man-machine resistance exists in the mechanical assisted ventilation process of the myasthenia gravis patient.

The invention discloses an obstructive sleep apnea event typing method and device based on respiratory center driving characteristics, electronic equipment and a computer readable storage medium, and belongs to the technical field of medical detection technologies and sleep medicine. According to the method, body surface diaphragm electromyographic signals and respiratory airflow signals of a subject are synchronously collected in a non-invasive mode, the body surface diaphragm electromyographic signals are preprocessed to obtain diaphragm electromyographic characteristic values, and the respiratory airflow signals are segmented and subjected to integral processing according to the respiratory cycle to obtain airflow characteristic values; selecting a characteristic value corresponding to at least one respiratory cycle before the event occurs as a reference baseline, calculating a diaphragm myoelectricity change value and an airflow change value of each respiratory cycle in the event relative to the reference baseline, and calculating the diaphragm myoelectricity change value based on a coupling relationship between the airflow change value and the diaphragm myoelectricity change value, and performing central drive dependent or non-central drive dependent judgment on the obstructive sleep apnea event. The method can provide technical support for typing analysis of the obstructive sleep apnea event.

The invention is suitable for the technical field of medical equipment, and provides a medical equipment ventilation control method and system, a storage medium and medical equipment.The method comprises the steps that initial ventilation pressure is calculated according to the target tidal volume and respiratory mechanical parameters measured through tentative ventilation, and the initial ventilation pressure is applied to pressure control ventilation of the first respiratory cycle; the actual tidal volume of each respiratory cycle is monitored in real time, and whether the target tidal volume is reached within the target inspiration time or not is judged; if not, the ventilation pressure of the next respiratory cycle is adjusted according to the actual tidal volume and the target tidal volume; if yes, whether the actual inspiration time is smaller than the target inspiration time is judged; and if the actual inspiration time is less than the target inspiration time, immediately stopping the ventilation flow rate to enter an inspiration pause stage, and dynamically adjusting the ventilation pressure of the next respiratory cycle according to the actual inspiration time and the target inspiration time of each respiratory cycle until the actual inspiration time is equal to the target inspiration time. The problem of tidal volume overshoot possibly generated under an existing pressure adjusting mechanism is solved.

The invention relates to the technical field of auxiliary medical treatment, in particular to an oxygen generator on-demand pulse oxygen supply control method based on respiratory rhythm perception, and the method comprises the steps: obtaining a plurality of respiratory pressure sequences, and dividing the respiratory pressure sequences into an expiratory phase and an end-expiratory transition section; determining a signal confidence coefficient according to the performance of the expiratory phase and the end-expiratory transition section in the respiratory pressure sequence; a regularization item of physiological rationality constraint is introduced into the regression loss function, and time sequence smooth constraint is applied to a model cell state updating process to obtain an optimized respiratory rhythm prediction model; taking the three-dimensional feature vector as input data of a respiratory rhythm prediction model to obtain an end-expiratory stationary section duration ratio of a next respiratory cycle; and determining a pre-judgment window period from the beginning of inspiration according to the duration proportion of the end-expiratory stationary section of the next respiratory cycle, and controlling pulse oxygen supply of the oxygen generator by taking the pre-judgment window period as a pulse trigger countdown parameter of the oxygen generator, thereby realizing accurate synchronization of the oxygen supply action and the inspiration action.

The invention relates to a sampling device, in particular to a sampling device for real-time continuous analysis of end expired gas. Comprising first to fourth three-way valves, a first sampling ring, a second sampling ring, an air pump, a purging pipeline, an exhalation pipeline, a carbon dioxide sensor and an analysis detector, the air inlets of the first sampling ring and the second sampling ring are connected with a purging pipeline through a first three-way valve and are connected with an exhalation pipeline provided with a carbon dioxide sensor through a second three-way valve; air outlets of the first sampling ring and the second sampling ring are connected with an analysis detector through a third three-way valve and are connected with an air pump through a fourth three-way valve; through linkage switching of the first three-way valve, the second three-way valve and the third three-way valve, the fourth three-way valve and the fourth three-way valve, the first sampling ring and the second sampling ring alternately conduct sampling and sample injection, and real-time accurate sampling and continuous sample injection analysis of tail end expired gas in each respiratory cycle are achieved. The device is high in time resolution, accurate in terminal expired gas sampling, constant in volume and good in detection result consistency.