148 results about "Respiratory cycle" patented technology

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 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.

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 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 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 discloses an intelligent ward risk assessment method and system, a product and a medium. The method comprises the following steps: synchronously monitoring breathing audio and mattress pressure signals of a patient, and identifying discrete action events with remarkable amplitude and duration from pressure data; further judging whether the breathing of the patient is abnormal or not before and after the action events occur, for example, the breathing rhythm is interrupted for a long time or the breathing cycle obviously deviates from a baseline; when the two conditions of the violent action and the abnormal breathing cooperatively occur, an effective cooperative event record is confirmed; according to the amplitude and the duration of the action in the event and the severity of the abnormal breathing, weighted summation is carried out through a preset risk weight, and a single event risk score is calculated; and accumulating all event risk scores in an evaluation period to obtain a comprehensive risk score, comparing the comprehensive risk score with a risk threshold, and outputting a risk level. By implementing the technical scheme provided by the invention, the accuracy of clinical compound action risk early warning of the patient is improved.

The invention relates to the technical field of clinical decision support and medical data intelligent analysis, in particular to a critical patient individualized liquid resuscitation decision support system, which is characterized in that a data acquisition unit acquires pulse pressure variation waveform and multi-dimensional physiological data of each stroke volume; a volume benefit analysis channel of the dynamic decision-making unit segments a respiratory cycle, extracts pulse pressure fluctuation characteristics, outputs a per-stroke volume increase probability value through a machine learning classifier, an organ injury early warning channel calculates a blood lactic acid and creatinine clearance rate change rate, and generates an acute kidney injury risk sign in combination with inferior vena cava image verification; the execution control unit sends an infusion control or limit instruction according to the combined state; and the feedback optimization unit adjusts the weight of the model according to the actual value of blood lactic acid removal, and recalculates the probability value, so that individualized precise resuscitation, balance capacity benefit and organ protection are realized, and the treatment safety and effectiveness are improved.

The invention provides a breathing guide interaction method and equipment. The method comprises the following steps: acquiring a breathing waveform signal of a target object; determining a rhythm stability index and an amplitude mutation detection index of the target object in each respiratory cycle based on the respiratory waveform signal; in response to the condition that the duration of the rhythm stability index and the amplitude mutation detection index meeting the corresponding stability conditions is greater than or equal to a first preset duration, sending prompt information representing the start of respiratory guidance; an inspiration demonstration action is displayed through the interactive interface, an inspiration prompt instruction is sent, and the curve slope in the inspiration waveform signal is detected; in response to the fact that the time when the curve slope is smaller than a first preset threshold exceeds a second preset duration, displaying an expiration demonstration action through the interactive interface and sending an expiration prompt instruction; and in response to the fact that the time when the curve slope is smaller than a second preset threshold exceeds a third preset duration or the expiration stage duration exceeds a fourth preset duration, sending an expiration termination instruction.

The application relates to a sampling device, in particular to a sampling device for real-time continuous analysis of end-exhaled air. The sampling device comprises first to fourth three-way valves, a first sampling ring, a second sampling ring, an air suction pump, a purge gas pipeline, an exhaled air 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 the purge gas pipeline through the first three-way valve and connected with the exhaled air pipeline provided with the carbon dioxide sensor through the second three-way valve; the air outlets of the first sampling ring and the second sampling ring are connected with the analysis detector through the third three-way valve and connected with the air suction pump through the fourth three-way valve; through linkage switching of the first to fourth three-way valves, the first sampling ring and the second sampling ring alternately carry out sampling and sampling, real-time accurate sampling of end-exhaled air in each breathing cycle and continuous sampling analysis are realized. The application has high time resolution, accurate end-exhaled air sampling and constant volume, and good consistency of detection results.

The invention provides a driver emotion information determination method which can be applied to the technical field of radars. The method comprises the following steps: transmitting a radar signal to a driver through a radar module mounted at a preset position in a driver seat, and receiving an echo signal obtained by reflecting the radar signal by the driver; extracting a heartbeat cycle and a breathing cycle of the driver from the echo signal, wherein the heartbeat cycle comprises I heartbeats; calculating a heartbeat interval change rate representing heart rate variability based on every two adjacent heartbeat cycles in the I heartbeats and the I heartbeats; calculating a respiratory rate based on the respiratory cycle; and determining the emotional state of the driver based on the heartbeat interval change rate and the breathing rate. The invention further provides a driver emotion information determination device, equipment and a storage medium.

One aspect of the invention relates to an elastography method implemented by an elastography device, the method comprising:-obtaining a respiratory signal relating to a respiratory activity of a subject; and-acquiring a plurality of measurements of a mechanical property of a region of the body of said subject, said region being part of the liver or spleen of said subject, at a repetition rate of at least 4 measurements per second and over a duration of at least 3 seconds; -extracting at least one subset of measurements from the plurality of measurements, where each subset of measurements among the at least one subset of measurements comprises measurements acquired at the same time of a respiratory cycle, the time of the respiratory cycle being determined from the respiratory signal; -determining a characteristic relating to said mechanical property from said at least one subset of measurements.

A physiological information display apparatus includes a heart rate acquisition unit configured to acquire a heart rate of a subject, a respiration rate acquisition unit configured to acquire a respiration rate of the subject, a hemodynamics calculation unit configured to calculate a hemodynamic parameter of the subject, and a respiratory variation of the hemodynamic parameter, based on a plurality of the hemodynamic parameters calculated in a predetermined period, and a display controller configured to output the respiratory variation to a display. The hemodynamics calculation unit is configured to calculate a heart rate in one respiration. The display controller is configured to output a setting screen for setting a length of the predetermined period. The hemodynamics calculation unit is configured to acquire setting information, set the length of the predetermined period based on the acquired setting information; and calculate the respiratory variation in the set predetermined period.

The invention discloses a seat, and belongs to the technical field of seats. The seat comprises a seat back structure; the pressure sensor is arranged on the chair back structure; the waist support module comprises at least one air bag assembly, and the waist support module is arranged on the chair back structure; the controller is connected with the pressure sensor and the waist support module, and is used for determining a corresponding predicted breathing state of a target object in a next time period of a target time period based on pressure information, collected by the pressure sensor, of the target object on the seat in the target time period, and determining the corresponding predicted breathing state of the target object in the next time period of the target time period based on the predicted breathing state. And controlling the inflation volume of the at least one airbag assembly in the next time period. According to the seat, the supporting force of the waist supporting module can be dynamically adjusted along with the breathing rhythm of the user, the fitting degree of the waist supporting module and the waist of the user is improved, gapless supporting in the whole breathing period is achieved, and the use experience of the user is improved.

A medical robot (10) comprises a robotic arm (13) equipped with a tool guide (14) for guiding a medical instrument (15) along a trajectory defined by an entry point at the patient's skin and a target point at a lesion to be treated in an anatomy of interest of the patient. The medical robot cooperates with an ultrasound probe (40) and with a navigation system (30) for determining the position of the robot, the position of the ultrasound probe, and the position of a patient marker (22). The robot is configured to generate a model of the position of the target point and the position of the entry point according to the position of the patient marker on the basis of ultrasound images acquired by the ultrasound probe during at least one respiratory cycle of the patient. The model thus generated then allows the robotic arm to be controlled in real time according to the position of the patient marker in order to guide the medical instrument with precision.

FIELD: cardiology.SUBSTANCE: used as a component of the first stage of cardiac rehabilitation in patients with chronic heart failure (CHF), as well as an auxiliary component at all stages of cardiac rehabilitation. Warm-up exercises are performed – stretching exercises and movements in the joints of the upper body, followed by a basic set of breathing exercises lasting from 15 to 30 minutes, at least once a day, at least 5 days a week, for at least 8 weeks. At the first stage, the main set of exercises includes four exercises performed in sequence: abdominal breathing, chest breathing, breathing involving the shoulder muscles, breathing slowing. The first three exercises are performed for 5–10 breathing cycles with an interval between exercises of at least 1 minute, the fourth exercise contains 5–15 cycles, where each cycle includes an inhalation through the first nostril, followed by an exhalation and inhalation through the second nostril, then an exhalation through the first nostril . In the second and subsequent stages, the main set of exercises includes two exercises performed sequentially: an exercise for full breathing and an exercise for slowing down breathing. The full breathing exercise involves sequentially performing abdominal breathing, chest breathing, and breathing with the involvement of the shoulder muscles throughout one inhalation. The exhalation is performed in reverse order. The number of cycles of the full breathing exercise at the second stage is 15–20. The duration of each stage is at least 2 weeks, where at each subsequent stage, starting from the second one, the duration of the exercises performed in the main complex is increased by increasing the number of exercise cycles. Also the duration of inhalation and exhalation is increased when performing exercises to slow down breathing. The method improves the biomechanics of breathing: increases the depth of breathing, reduces the frequency of respiratory movements, increases the efficiency of breathing and reduces the activity of the inspiratory metaboreflex.EFFECT: exercise tolerance in patients with CHF improves.3 cl, 6 dwg, 3 ex

The invention provides an air bag pressure linkage adjusting method and system based on airway peak pressure feedback, relates to the technical field of medical equipment control, and aims to solve the problems of control algorithm lag, lack of linkage mechanism, poor clinical practicability, insufficient safety redundancy and the like in the prior art. According to the method, on the basis of airway peak pressure values of a plurality of continuous breathing cycles, an air bag pressure target value is increased in a stepped mode one by one in the breathing cycles, and stable state judgment is synchronously conducted till the airway peak pressure is stable; in the stable maintaining stage, the airway peak pressure is continuously monitored, and if the rise exceeds a preset fluctuation threshold value, the current locking target value is taken as the reference to be increased step by step again according to the preset step length; and if the reduction exceeds the preset fluctuation threshold value, the target value is reset as the initial airway peak pressure, and step adjustment is performed again until the airway peak pressure is stabilized again. The problems existing in the prior art are solved, and dynamic cooperative adjustment of the airway peak pressure and the airbag pressure is achieved.

This invention belongs to the field of nasal alar pulse wave signal processing technology, and provides a method, apparatus, medium, and wearable device for nasal alar pulse wave signal processing. The method includes: extracting the respiratory cycle based on the respiratory signal; determining the length of the mean sliding filter window to filter out the DC component of the original nasal alar pulse wave signal, obtaining a filtered nasal alar pulse wave signal; extracting the amplitude of the AC component of the filtered nasal alar pulse wave signal; adjusting the current of the light source element corresponding to the pulse wave signal sensing element to make the amplitude of the AC component of the filtered nasal alar pulse wave signal greater than or equal to a preset amplitude threshold; further filtering the nasal alar pulse wave signal using an adaptive weighted moving average filtering algorithm; and determining whether a nasal alar pulse wave signal meeting preset quality requirements is obtained based on a comparison between the noise figure of the further filtered nasal alar pulse wave signal and a preset noise figure threshold.

The present application relates to the technical field of medical image analysis, in particular to a patient post-anesthesia pain grading evaluation method based on artificial intelligence. The method acquires multi-time body posture images in a complete respiratory cycle, constructs a trunk reference system, defines the end of the limb as an analysis point and a preset defense position as a target point; constructs a limb scheduling consumption matrix based on the distance between the analysis point and the target point, calculates the limb wandering confusion degree combined with the element distribution, and fuses to obtain the defense intention focus degree reflecting the order of whole body movement; the consumption matrix is subjected to geometric cost matching to obtain a limb scheduling total consumption index, and the focus degree is combined to generate a defense interference index; finally, the grading evaluation coefficient is determined according to the numerical distribution and stability of the index in the complete respiratory cycle, thereby objectively distinguishing the pain state and the wake-up period agitation state, and significantly improving the automation level and reliability of post-anesthesia pain evaluation.

The application discloses a point cloud driven thoracic cavity whole organ dynamic reconstruction and respiratory monitoring method and system, and the method implementation comprises the following steps: based on the thoracic medical image data of a target object, constructing three-dimensional geometric models corresponding to each target structure in the thoracic cavity, and converting the three-dimensional geometric models into static point cloud data; based on the respiratory motion law of the target object, driving the static point cloud data to perform dynamic deformation simulation in a respiratory cycle, and obtaining dynamic point cloud data synchronized with the respiratory phase; synchronously associating the dynamic point cloud data with electrical characteristic parameters in time and space, and constructing a digital twin thoracic cavity model; deploying a virtual sensor assembly that dynamically deforms with the thoracic cavity in the digital twin thoracic cavity model, and simulating and monitoring the dynamic respiratory process of the target object, and generating a virtual physiological signal; and through signal processing on the virtual physiological signal, a dynamic reconstruction image reflecting the respiratory motion is obtained. The continuous simulation of the whole respiratory motion process is realized, and the time and space resolution and diversity of the virtual database are improved.

The present application relates to the technical field of respiratory monitoring, in particular to a big data intelligent health respiratory dynamic monitoring method, system and terminal. According to the change characteristics of the respiratory pressure signal, the time domain interval of each respiratory cycle is obtained; further, the work amount corresponding to each respiratory cycle is obtained, and the respiratory mode is divided; further, the latest seasonal cycle of the respiratory pressure signal is extracted, according to the change characteristics of the work amount of the time series adjacent respiratory cycles in the seasonal cycle, combined with the number distribution characteristics of the respiratory cycles of the respiratory mode, the respiratory stability coefficient is obtained; further, when the respiratory stability coefficient is greater than or equal to the preset stability threshold, the predicted respiratory pressure signal is obtained and verified, and finally the predicted respiratory mode is obtained according to the final predicted respiratory pressure signal, the hysteresis of real-time processing is reduced, the response speed of respiratory support is improved, and the comfort is improved.

The present application provides a kind of respiratory guidance interaction method and equipment, the method comprises: obtaining the respiratory waveform signal of target object;Respiratory waveform signal is based on determining the rhythm stability index and amplitude mutation detection index of target object in each respiratory cycle;In response to rhythm stability index and amplitude mutation detection index each respectively comply with the duration of corresponding stability condition greater than or equal to first preset time length, send the prompt information characterizing respiratory guidance start;Through interactive interface, inhale demonstration action is shown and inhale prompt instruction is sent, and the curve slope in respiratory waveform signal is detected;In response to the time when curve slope is less than first preset threshold value exceeds second preset time length, through interactive interface, exhale demonstration action is shown and exhale prompt instruction is sent;In response to the time when curve slope is less than second preset threshold value exceeds third preset time length or the length of time when exhale stage exceeds fourth preset time length, send exhale termination instruction.

The invention discloses an electronic control method of a medical laser positioning system, which comprises the following steps: a signal acquisition and conversion step: acquiring an optical signal reflected by positioning laser on the body surface of a patient and modulated by respiratory movement, and converting the optical signal into a corresponding sensing electric signal; phase identification: processing the sensing electric signal to identify whether the current respiratory cycle is in a preset stable phase or not; a laser gating step of controlling the output mode of the positioning laser according to the identification result of S2; when the positioning laser is identified to be in the preset stable phase, the positioning laser is controlled to work in a first output mode, and the laser positioning system is upgraded from a passive projection tool to an active system with the physiological signal sensing capacity. By extracting the breathing phase in real time and accurately controlling the laser output mode according to the breathing phase, the system can automatically provide a clear positioning mark at the most stable moment in the breathing cycle.

The invention discloses an intelligent control method and system for a noninvasive respirator, and relates to the technical field of intelligent control of respirators. According to the method, airway flow and pulse wave signals are obtained through signal collection and respiratory phase recognition, the end-expiratory pause time period is positioned, a time-frequency image is constructed and preprocessed to obtain a high-resolution enhanced time-frequency energy image, and cardiac oscillation components are recognized and separated to obtain pure respiratory flow signals. The autonomous inspiration effort is judged through double triggering conditions, and air supply control is achieved; verifying parameters are evaluated and adaptively updated based on the respiratory cycle, and personalized configuration parameters are locked; the problems of false triggering and leakage triggering air supply caused by cardiac airway flow oscillation interference generated by cardiac pulsation in the ventilation process of the noninvasive breathing machine are effectively solved, and the accuracy and reliability of air supply triggering of the breathing machine are remarkably improved.

The application discloses a mesh nebulizer. The nebulization control method of the mesh nebulizer comprises the following steps: acquiring breathing data of a user; determining a breathing state of the user and an end time point of exhalation of each breathing cycle based on the breathing data; the breathing state comprises stable breathing and abnormal breathing; and controlling a running state of a nebulization sheet based on the breathing state and the end time point of exhalation. According to the breathing state of the user and the end time point of exhalation, the running state of the nebulization sheet is accurately controlled, so that the drug utilization rate is improved, and intelligent and personalized nebulization treatment is realized.

A mechanism for guiding the length of a multitude of different segments across a multitude of breathing cycles. A recorded length of each of the multitude of segments is obtained in a sample breathing cycle. The recorded length of each segment, along with a sample breathing rate and a desired breathing rate, is used to define a target length for each segment in each of the multitude of breathing cycles. Each target length is proportional to the corresponding recorded length.

The application relates to the technical field of intelligent vehicle-mounted technology, in particular to a breathing synchronization intelligent vehicle-mounted oxygen supply control method and system, which comprises the following steps: emitting electromagnetic waves to passengers through a millimeter wave radar and receiving reflected echo signals; performing signal processing on the reflected echo signals to obtain periodic signal waveforms; identifying the inspiration stage and the expiration stage of the passengers based on the periodic signal waveforms; outputting an opening instruction in response to the identification of the inspiration stage; outputting a closing instruction in response to the identification of the expiration stage; and based on the analysis of the periodic signal waveforms formed by the passengers in a plurality of historical breathing cycles, predicting the starting moment of the next inspiration stage and outputting the opening instruction at a preset time point before the predicted starting moment of the inspiration stage. The oxygen utilization rate is greatly improved, so that a smaller-power oxygen generator or a smaller-capacity oxygen storage tank can be used under the condition of the same effective oxygen uptake, thereby reducing the system volume, weight, cost and energy consumption.

A method for determining rebreathed gas fractions in a respiratory gas supply system using specific respiratory or ventilation parameters, wherein the expiratory flow and the leakage flow are recorded during a respiratory cycle, the expiratory and leakage volumes resulting from the integration of these two flows are determined, and the rebreathing fraction (VR) is determined as the difference between the expiratory volume and the leakage volume (VR = VE - VL), and an alarm is generated if a critical value for the determined FiCO2 is exceeded or if VR > 0, characterized in that, if VR > 0, the fraction of CO2 in the subsequent inspiration that is formed at the end of inspiration by the mixing of rebreathed air with fresh air in relation to the total inspired volume in the lungs (FiCO2) is estimated, and wherein the estimation of FiCO2 is carried out taking into account anatomical dead spaces.