11 results about "Pulmonary compliance" patented technology

The invention discloses an EIT-based respiratory muscle force and lung compliance closed-loop evaluation system, which is characterized by comprising a multi-frequency EIT injection / sampling unit, a signal processing unit and a signal processing unit, a pressure measurement and synchronization unit; an FPGA clock synchronization triggering unit; an EIT preprocessing unit; a compressed sensing reconstruction unit; a [delta] Z-Pressure fitting unit is adopted; a feature extraction unit; a control decision unit; and the self-adaptive NMES participates in a trend recording unit. According to the method, advanced technologies such as multi-frequency EIT, compressed sensing reconstruction, machine learning fitting, fuzzy + PID mixed control and federated learning are integrated, a new normal form for closed-loop evaluation and optimization of respiratory muscle force and lung compliance is created, and the method has great clinical value for rehabilitation of diseases such as COPD and neuromuscular respiratory failure.

The invention discloses a breathing module turbine variable speed control method of a life support system, which relates to the technical field of medical equipment and comprises the following steps: acquiring relevant parameters of a motor connected with a turbine to be detected and a medical scene mode of a target user, and judging initial turbine rotating speed parameter information of a breathing module; detecting and based on the lung compliance of the target user, judging the demand of the lung state of the target user for the rotating speed of the turbine to be detected to obtain turbine rotating speed demand information; identifying whether the target user has interference in the use process of the life support system, and if so, judging the influence of the target user on the rotating speed of the turbine to be detected to obtain a first type of disturbance rotating speed influence value; whether the breathing module vibrates or not in the using process of the turbine to be detected in the breathing module is recognized, and if yes, the influence of equipment vibration on the rotating speed of the turbine to be detected is judged, and a second type disturbance rotating speed influence value is obtained. The method has the effect of improving the turbine variable speed control precision of the breathing module of the life support system.

A test platform for simulating patient conditions. In accordance with methods, systems, platforms and modules, the controller of a ventilator, may be tested. Where the ventilator manages automated mechanical ventilation controllers' maintenance of peripheral oxygen saturation (SpO2) for a simulated patient, an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FiO2) and the peak inspiratory pressure ventilator settings of the ventilator is tested by a test platform controller. Where the ventilator manages end-tidal carbon dioxide (EtCO2) of a simulated patient, operation of the test platform controlled by the platform controller of the test platform in providing carbon dioxide generation, lung compliance (CL) and airway resistance (RAW) states while providing an EtCO2 level that is responsive to changes in tidal volume and respiratory rate changes of the patient is tested.

A method for ventilating a patient includes providing pressure into a patient's airway over a period of time that includes a plurality of inhalation periods and a plurality of exhalation periods. The pressure is at an inspiratory positive airway pressure during the inhalation periods, and the pressure is at an expiratory positive airway pressure during the exhalation periods. The expiratory positive airway pressure less than the inspiratory positive airway pressure, and the expiratory positive airway pressure is configured to maximize lung compliance of the patient.

This invention discloses a method for estimating airway resistance and compliance. The method includes: acquiring multiple sets of sampled data and acquiring a preset discrete nonlinear airway resistance model. Each set of sampled data includes airway pressure, total flow rate, and tidal volume sampled at a single sampling time. Based on the multiple sets of sampled data and a pre-established parameter update model, preset parameters in the discrete nonlinear airway resistance model are solved to obtain parameter values. Based on the parameter values ​​and the substitution relationships between the preset parameters and linear airway resistance, nonlinear airway resistance, and lung compliance, linear airway resistance, nonlinear airway resistance, and lung compliance are solved. The linear airway resistance and lung compliance are used to effectively control the ventilation modes of anesthesia machines and ventilators to suit various usage situations for different users. Furthermore, devices, equipment, and media for estimating airway resistance and compliance are also proposed.

PEEP-valves configured to be placed inline with the exhalation path of a ventilator and ahead of the exhalation valve. The PEEP-valve functions as a resistor that can provide a higher PEEP value for any given PIP, lung compliance, and respiratory rate combination compared to a standard PIP to PEEP ratio.

The invention belongs to the field of traditional Chinese medicines, and discloses a traditional Chinese medicine composition for treating qi deficiency and blood stasis type idiopathic pulmonary fibrosis as well as a preparation method and application thereof. The traditional Chinese medicine composition disclosed by the invention is prepared from astragalus membranaceus, angelica sinensis, raw oyster, honey-fried aster, scutellaria baicalensis and the like, has the effects of tonifying qi, removing blood stasis, eliminating stagnation, clearing away lung-heat, relieving cough and asthma, and has a certain treatment effect on lung compliance reduction, gas exchange disorder and small airway resistance increase caused by lung tissue fibrosis. The long-term use is safe and effective.

The invention, which belongs to the technical field of the medical equipment, discloses a lung transplantation post-operative cardiopulmonary capacity collaborative evaluation and adjustment system comprising a multi-parameter acquisition module, a cardiopulmonary interaction modeling module, a capacity strain test module, a haemodynamics target setting module, a treatment response prediction module and an adjustment execution module. The system quantitatively analyzes the complex relationship among the right heart function, the pulmonary vascular resistance and the pulmonary compliance through a cardiopulmonary interaction modeling engine, evaluates the tolerance of a patient to the capacity change through a capacity strain test, and formulates an individualized hemodynamic target according to a specific cardiopulmonary interaction mode of the patient. Potential influences of different intervention measures are simulated, treatment parameters are automatically adjusted, the hemodynamic stability and the oxygenation function of a lung transplantation patient are remarkably improved, and the occurrence rate of complications is reduced.

The invention relates to the technical field of respirator control, in particular to an intelligent parameter matching method of an anesthesia respirator based on a self-adaptive algorithm, which comprises the following steps of: executing inspiration blocking inversion static flow resistance coefficient at the initial stage of starting the anesthesia respirator, mapping pressure drop by combining real-time flow velocity and reconstructing real-time pulmonary alveolar estimation pressure, and calculating the real-time pulmonary alveolar estimation pressure; integrating the flow velocity to obtain the tidal volume so as to construct a pressure volume sequence and a dynamic linear compliance reference standard, quantifying trajectory deviation, generating inspiration phase and expiration phase nonlinear deviation total moment through trapezoidal integral operation, judging the lung compliance state according to the total moment, executing negative feedback correction, and generating a target tidal volume parameter. By blocking inversion flow resistance coefficient mapping pipeline pressure drop and reconstructing signals to isolate alveolar pressure to eliminate interference, a dynamic compliance reference is constructed, a lag moment is utilized to quantify a deviation track, a state is accurately identified, the tidal volume is corrected in a negative feedback mode, ventilation self-adaptive matching is achieved, and the problems of monitoring lag and parameter mismatching are solved.

This invention relates to the field of lung compliance prediction technology, specifically to a method, application method, and system for training a lung compliance prediction model. The training method includes: acquiring sample data; training a pre-defined prediction model using multi-parameter curve data and corresponding lung compliance values ​​from the samples to obtain a lung compliance prediction model; during training, the prediction model outputs predicted lung compliance values ​​based on the parameter curve data, and updates the trainable parameters in the model through an error backpropagation mechanism based on the error between the predicted lung compliance value and the corresponding lung compliance value. The trainable parameters include convolutional layer parameters in the feature extraction module and fully connected layer parameters in the regression prediction module. This invention can utilize data from lung function testing devices such as spirometers (e.g., parameter curves) for non-invasive, non-surgical prediction of lung compliance.

The present application belongs to the technical field of medical diagnostic measurement, and relates to a lung compliance dynamic monitoring system based on respiratory loop pressure waveform decoupling, comprising: a sensing driving and registration module for acquiring output filtered real-time pressure and instantaneous flow sequence; a time sequence mask stream generation module for generating a Boolean time sequence mask in combination with a flow gradient and a threshold value; a resistance factor extraction module for updating and locking a real-time airway resistance factor according to a mask logic; a multi-stage pressure decoupling module for extracting temporary elastic pressure by deducting resistance pressure drop and reference pressure from the aforementioned sequence; an abnormal data elimination module for eliminating abnormal data and outputting an effective elastic pressure signal according to a threshold value; and a solving and feedback module for determining a compliance sequence by dividing the flow integral volume by the pressure, and extracting a trend feedback parameter adjustment. The present application solves the problem of how to decouple and continuously monitor the dynamic changes of lung compliance in real time from the airway pressure waveform in the airflow environment containing non-autonomous interference and mechanical noise.