216 results about "Respiratory cycle" patented technology

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 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.

An example computer system analyzes nasal airflow data to detect sleep disorders. The system can estimate the breathing cycle frequency on the pressure nasal airflow data. Based on this frequency, the system can calculate optimal smoothing window sizes. The system can perform a smoothing operation on the airflow data and auxiliary sensor data using these windows. Breathing cycles can be detected in the smoothed data streams. Cycles meeting artifact conditions but not sigh conditions can be removed as noise. Remaining clean cycles can be analyzed further. A transition segment between the peak of one cycle and trough of the next can be classified. Using this classification and the cleaned auxiliary data, the system can detect sleep disorder events.

The invention relates to the technical field of respiratory health monitoring, and discloses a remote respiratory health monitoring and management system and method. The method comprises the steps that an original respiration data set containing time sequence and frequency domain characteristics is collected through a multi-mode sensor, respiration cycle segments are divided through dynamic segmentation processing, key waveform mark points are extracted, and a respiration state transition network is constructed to form a dynamic topological structure. And generating a breathing environment coupling matrix in combination with environmental parameters, screening interfered abnormal breathing segments, training an analysis model to output a deviation score, triggering multi-level early warning and generating a report containing a backtracking path. User activity log timestamps are matched through cross-device verification, data are integrated to construct a breathing behavior association map, a model judgment threshold value is updated based on the map, and monitoring closed-loop feedback is completed. According to the method, accurate monitoring and dynamic management of respiratory health are achieved, and a complete solution is provided for remote respiratory health management and control.

The invention provides a sleep physiological parameter real-time monitoring method based on flexible piezoelectric sensing, and relates to the technical field of biomedical signal processing.The method comprises the steps that a human body sleep biological mechanical signal is collected through a flexible piezoelectric sensor array, and after the signal is converted through a charge amplifier, phase-space reconstruction denoising and self-adaptive gain control are carried out; wherein the gain is dynamically adjusted based on the weight of the user, the rigidity coefficient of the mattress and the real-time signal amplitude; extracting heartbeat wave crest intervals, respiratory cycles and body movement frequency domain energy characteristics from the preprocessed signals; inputting the features into a cascaded convolutional neural network and a long-short-term memory network model, and synchronously outputting the heart rate, the respiration rate and the heart rate variability; in combination with the historical health data of the user and the cardiovascular health mapping model, sleep quality indexes and disease risk scores are generated through graph convolutional network analysis, and the monitoring frequency is dynamically adjusted and an apnea alarm is triggered.

The invention discloses a three-dimensional in-vivo radiotherapy dose monitoring method and system, and the method comprises the steps: collecting an image sequence {In} containing time dimensions at a theta t time interval through CBCT scanning equipment in a radiotherapy process; calculating target area displacement of adjacent frames of images in the image sequence {In} by using a bidirectional optical flow estimation method; state estimation and prediction are carried out on the displacement data based on an adaptive Kalman filtering algorithm, a dynamic displacement rule of the target area in the respiratory cycle is generated, and a respiratory movement prediction result is output; acquiring radiotherapy plan parameters from a radiotherapy plan system, and calculating planned dose distribution without considering respiratory movement; dynamically adjusting a ray transmission path and energy deposition according to a respiratory movement prediction result, and calculating real-time dose distribution of each respiratory time phase; mapping the dose distribution of each time phase to a reference time phase coordinate system to generate accumulated dose distribution; and comparing and verifying the accumulated dose distribution and the planned dose distribution.

The invention provides a multi-modal image registration method and system based on a deformation field, a storage medium and equipment, and the method comprises the steps: obtaining multi-modal images, including a 2D ultrasonic image and a 3D reconstruction image, and carrying out the coarse registration; obtaining a 2D ultrasonic image sequence of continuous frames, and obtaining rigid change parameters of the organ in a respiratory cycle; acquiring organ contour feature data points of each frame of 2D ultrasonic image, and performing elastic registration to obtain a 2D elastic deformation field of the organ; constructing a 2D-3D deformation function of the organ, and obtaining a 3D deformation field in a three-dimensional space; and updating vertex coordinates of the target organ in the 3D reconstruction image according to the 3D deformation field to obtain a mapped three-dimensional image to represent rigid and elastic changes of the organ. According to the method, by fusing the multi-modal image information and combining rigid and elastic deformation analysis, accurate registration of the ultrasonic image and the CT / MRI image is achieved, and the precision of multi-modal medical image registration is effectively 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.

Systems and methods for lung function parameters are disclosed herein. An electrocardiographic (ECG) device acquires ECG signals from a patient during a breathing cycle. A neural network trained to perform ECG-derived respiratory (EDR) analysis extracts respiratory information from the acquired ECG signals. A processor accesses the neural network. Respiratory features are extracted from the ECG signals. A forced expiratory volume (FEV1) of the patient during the breathing cycle is determined using the respiratory features. A report of lung function is generated using the FEV1.

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.

The invention belongs to the technical field of anaesthesia machines, and relates to an automatic target control method for the concentration of end-expiratory anesthetic gas of an anaesthesia machine and the anaesthesia machine. Calculating the deviation between the concentration of the end-expiratory anesthetic gas exhaled in the current respiratory cycle and a gas concentration set value; when the deviation and / or the change amount of the end-expiratory anesthetic gas concentration is larger than the threshold value, the flow of fresh gas used for flushing the anesthetic respiratory system is increased, and the anesthetic gas concentration of the fresh gas is adjusted till the deviation and the change amount of the end-expiratory anesthetic gas concentration are smaller than the threshold value; calculating predicted values of the concentration of the end-expiratory anesthetic gas in a plurality of future respiratory cycles; an anesthetic gas concentration optimization model is constructed and solved to obtain the optimal inhaled anesthetic gas concentration variation of each future respiratory cycle, so that the target flow of the fresh gas of each future respiratory cycle is calculated to control the conveying parameters of the fresh gas, and the final-expiratory anesthetic gas concentration is taken as an adjusting target to adjust the flow rate of the fresh gas. And the concentration of the end-expiratory anesthetic gas is effectively controlled through real-time feedback, dynamic prediction and adjustment.

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.

Neurostimulation therapy can be efficiently controlled based on information from an acceleration signal, such as can be obtained from an accelerometer. In an example, the accelerometer can be implanted in a cervical region or submandibular region of a patient. Circuitry can be configured to identify a first series of respiration phase transition events in the acceleration signal and, in response, provide the neurostimulation therapy synchronously with an inspiration phase of a patient's respirator cycle. In an example, m absence of identifying the first series of respiration phase transition events in the acceleration signal, the neurostimulation therapy can be provided asynchronously with the patient's respiratory cycle.

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.