Search

CN-122006056-A - Intelligent ventilator humidifying device with self-adaptive adjusting function and method

CN122006056ACN 122006056 ACN122006056 ACN 122006056ACN-122006056-A

Abstract

The invention relates to the technical field of medical equipment, in particular to an intelligent breathing machine humidification device with a self-adaptive regulation function and a method thereof, comprising a breathing machine main body and a humidification module, wherein the humidification module is arranged on the breathing machine main body and comprises a multi-source sensing module, a preprocessing and computing previewing module, an instant feedback and AI control module, an energy consumption calculation and regulation early warning module and a humidification water supplementing module, wherein the multi-source sensing module is used for collecting the temperature and humidity of inhaled gas at the near end of an airway of a patient in real time, and the multi-dimensional data of the patient is collected in real time, the humidification trend is predicted by utilizing a digital twin model, and the output is dynamically regulated based on the multi-dimensional data.

Inventors

  • YU SIYUAN
  • MA JING
  • WANG LU

Assignees

  • 中国人民解放军总医院第二医学中心

Dates

Publication Date
20260512
Application Date
20260409

Claims (10)

  1. 1. The intelligent breathing machine humidifying device with the self-adaptive adjusting function comprises a breathing machine main body (1) and a humidifying module (2), and is characterized in that the humidifying module (2) is arranged on the breathing machine main body (1), the humidifying module (2) comprises a multi-source sensing module (210), a preprocessing and computing previewing module (220), an instant feedback and AI control module (230), an energy consumption calculation and regulation early warning module (240) and a humidifying and moisturizing module (250), wherein: The multi-source sensing module (210) is used for collecting the temperature and humidity and the breathing waveform of the inhaled gas at the near end of the airway of the patient in real time; The multi-source sensing module (210) is also used for detecting the water level of the humidification tank of the breathing machine, the temperature of the heating plate, the condensed water state of the pipeline and the temperature and the humidity of the ward environment; The preprocessing and computing previewing module (220) is connected with the multi-source perception module (210); the preprocessing and computing previewing module (220) is used for fusing and preprocessing the acquired data; the preprocessing and computing previewing module (220) performs high-fidelity simulation based on the constructed digital twin model of the humidification process so as to predict the temperature and humidity changes, water consumption and energy consumption trend of the air passage in different time scales in the future; The instant feedback and AI control module (230) is connected with the preprocessing and computing previewing module (220); The instant feedback and AI control module (230) is used for dynamically setting a target humidification range according to individual information of the patient and a prediction result; The instantaneous feedback and AI control module (230) also adjusts heating and humidifying output in real time based on a model predictive control algorithm, optimizes efficiency by inspiratory phase pulse compensation, and simultaneously performs anomaly detection and safety intervention; The energy consumption calculation and regulation early warning module (240) is connected with the instant feedback and AI control module (230) and the preprocessing and calculation previewing module (220); The energy consumption calculation and regulation early warning module (240) is used for establishing an energy consumption model, performing multi-objective optimization under the constraint of meeting humidification requirements, generating and executing an energy saving strategy comprising predictive preheating and peak-valley electricity optimization, and sending early warning to energy efficiency abnormality or maintenance requirements; the humidifying and moisturizing module (250) is connected with the instant feedback and AI control module (230) and the energy consumption calculation and regulation and control early warning module (240); the humidifying and moisturizing module (250) receives a control instruction, precisely executes humidifying through the adjustable power heating plate and the atomizing assembly, and realizes automatic maintenance of the water level of the humidifying tank and sterile water management.
  2. 2. The intelligent ventilator humidification device with adaptive adjustment function of claim 1, wherein the multi-source sensing module (210) comprises a patient-side sensing unit, a device-side sensing unit, and an ambient-side sensing unit, wherein: The patient end sensing unit comprises a miniature temperature and humidity sensor, a respiration waveform sensor and an end-expiration gas detection sensor, wherein: the miniature temperature and humidity sensor is integrated at the near end of the patient of the breathing machine pipeline and is used for monitoring the temperature and humidity of inhaled gas; The respiratory waveform sensor is used for collecting respiratory flow and pressure waveforms so as to identify airflow fluctuation and pressure rising characteristics caused by viscous sputum; the respiratory waveform sensor identifies waveform jitter characteristics caused by dry stimulus or cough; the end-tidal gas detection sensor is used for evaluating the water loss of the airway; The equipment end sensing unit comprises a humidifying tank water level sensor, a heating plate temperature sensor and an optical or weight sensor for monitoring the condensation water quantity of the pipeline; the environment end sensing unit comprises an environment temperature and humidity sensor and an atmospheric pressure sensor.
  3. 3. The intelligent ventilator humidification device with adaptive adjustment function of claim 2, wherein the preprocessing and computing previewing module (220) is configured to: the preprocessing and computing previewing module (220) preprocesses the data collected by the multi-source sensing module (210), and specifically includes: setting differential sampling frequency, filtering denoising, outlier rejection and data normalization according to the dynamic characteristics of parameters; The preprocessing and computing previewing module (220) constructs and runs a digital twin physical model of a humidification process fusing thermodynamic and mass transfer chemical equations, and is used for calculating quantitative relations among heating power, water temperature, evaporation rate, pipeline heat dissipation and condensate water generation; The preprocessing and computing previewing module (220) is further coupled with an LSTM time sequence prediction model trained based on historical data to conduct multi-time scale prediction, and specifically comprises: predicting the temperature and humidity change and condensation risk of the air passage in a short period (1-30 minutes); Predicting the water consumption and the energy consumption trend of the humidifying tank in the middle period (30-60 minutes); The effect of patient activity or changes in conditions on humidification demand is predicted over a long period (hours).
  4. 4. A smart ventilator humidification device with adaptive adjustment function according to claim 3, wherein the immediate feedback and AI control module (230) is configured to: the instant feedback and AI control module (230) is internally provided with a mode library containing personalized humidification parameters of different disease types, and can dynamically set and load a target humidification strategy according to the disease type, the current ventilation mode and the activity state of a patient; The instant feedback and AI control module (230) adopts a model prediction control algorithm, and generates and issues a control instruction to the humidification water supplementing module (250) based on a prediction result of the preprocessing and calculation previewing module (220), wherein the control instruction comprises an inhalation phase pulse type power compensation strategy for optimizing the instant humidification efficiency under high flow support; the instant feedback and AI control module (230) also performs predictive-execute-correct closed-loop control, compares the sensor feedback and the predicted value in real time, and triggers strategy readjustment when the deviation exceeds the limit; the instant feedback and AI control module (230) is also provided with a plurality of controllable modes of comfort priority, balance energy conservation and energy conservation priority in advance, and has the functions of abnormal detection and early warning of insufficient humidification, excessive condensed water and equipment faults.
  5. 5. The intelligent ventilator humidification device with adaptive adjustment function of claim 4, wherein the energy consumption calculation and regulation pre-warning module (240) is configured to: the energy consumption calculation and regulation early warning module (240) performs multi-objective optimization, and an objective function is to minimize total energy consumption under the condition that the safety constraint of the temperature and the humidity of the air passage is met, and accurately calculate the energy consumption distribution of each component such as heating, sensing, control and the like; The energy consumption calculation and regulation early warning module (240) generates and executes an energy saving strategy, and the energy saving strategy comprises the following steps: According to the energy management strategy of 'valley filling up' or 'peak clipping and valley filling' of the peak valley period of the hospital electricity consumption; predictive warm-up or power adaptive loop strategies performed based on predicted humidification demand changes; and a strategy for participating in demand response in linkage with the hospital energy management system.
  6. 6. The intelligent ventilator humidification device with adaptive adjustment function of claim 5, wherein the humidification water replenishment module (250) comprises an intelligent water level control unit, wherein: The intelligent water level control unit adopts a metal wire electrode to sample water level, and is connected with an external sterile water storage device through a control circuit taking a singlechip AT89C2051 and a high input impedance field effect tube K117 as cores, so that the functions of automatic water level supplement, automatic water full stop, low water level alarm and dry burning prevention of a humidifying tank are realized.
  7. 7. The intelligent ventilator humidification device with adaptive adjustment function of claim 6, wherein the humidification refill module (250) further comprises a condensate water management unit, wherein; the condensed water management unit monitors the amount of condensed water in the breathing pipeline through an optical or weight sensor and triggers an automatic liquid draining mechanism when the amount of condensed water reaches a preset threshold.
  8. 8. The intelligent ventilator humidification device with adaptive adjustment function of claim 7, wherein the humidification replenishment module (250) is configured to implement a humidification fluid replacement cycle management strategy that extends a safe replacement cycle of humidification fluid to 7 days based on monitoring and calculation of humidification water pollution factors.
  9. 9. The intelligent ventilator humidification device with the self-adaptive adjustment function according to claim 8, wherein the instant feedback and AI control module (230) and the energy consumption calculation and regulation early warning module (240) are in communication connection with a remote monitoring system, can transmit humidification status, early warning information, energy consumption data and equipment status to a nurse station or a cloud platform in real time, and can receive instructions from a hospital energy management system.
  10. 10. An intelligent breathing machine humidifying method with a self-adaptive adjusting function is characterized by comprising the following steps of: Starting a breathing machine, loading a personalized humidification parameter mode library corresponding to the disease type and ventilation mode of a patient, initializing a target humidification range, a safety threshold and an operation mode, and synchronously acquiring patient-side data, equipment-side data and environment-side data according to differential sampling frequency by a multi-source sensing module; Filtering, denoising, outlier rejection and normalization preprocessing are carried out on the acquired multi-source data, the preprocessed data is input into a humidifying process digital twin model fused with thermodynamic and mass transfer chemical physical equations, and high-fidelity simulation and multi-time scale prediction are carried out by coupling an LSTM time sequence prediction model trained based on historical data; The personalized target setting and strategy generation based on model prediction control are carried out, namely a target humidification parameter range is dynamically set or adjusted according to the real-time state of a patient and the prediction result of the step two, and based on a model prediction control algorithm, the total energy consumption of a minimum system is taken as one of optimization targets on the premise of meeting the target humidification parameter range and equipment safety constraint, multi-target optimization solving is carried out, an instant control strategy comprising a heating plate power adjustment curve, an atomization output instruction and an inhalation phase pulse type power compensation scheme in a future period is generated, and the process synchronously generates an energy-saving scheduling strategy linked with a peak-valley period of hospital use; Performing virtual simulation verification on the generated instant control strategy and energy-saving scheduling strategy in a digital twin model, after verification, issuing a control instruction to an execution unit, and accurately controlling a humidification process by the execution unit through adjusting the power of a heating plate and the output of an atomization component, and executing air suction phase pulse power compensation to optimize the instant humidification efficiency under high flow ventilation, and simultaneously executing a demand response strategy of the energy-saving scheduling strategy and the communication cooperation of a hospital energy management system; The intelligent water level maintenance, condensate water management and closed-loop correction are carried out by taking a singlechip AT89C2051 and a high input impedance field effect tube K117 as core intelligent water level control unit, automatically supplementing water from a sterile water storage device to a humidification tank according to the calculated water consumption trend, realizing automatic stop of water filling and low water level early warning, simultaneously monitoring the pipeline condensate water quantity through a sensor, triggering an automatic discharge mechanism when reaching a threshold value, comparing sensor feedback data with a predicted value of a digital twin model in real time, and triggering recalculation and adjustment of a control strategy to realize closed-loop control if the deviation exceeds a preset threshold value; Continuously monitoring humidification effect, system energy consumption and equipment operation state, detecting and early warning humidification deficiency, humidification excess, condensate water exceeding, energy efficiency abnormality and equipment fault in real time, transmitting humidification state data, early warning information, energy consumption report and equipment log to a remote monitoring system in real time, receiving a remote intervention instruction, dynamically managing and prompting a safe replacement period of humidification liquid according to calculation evaluation of humidification water pollution risk, recording operation data by the device, updating a digital twin model and a prediction model through online learning, and optimizing a personalized strategy library.

Description

Intelligent ventilator humidifying device with self-adaptive adjusting function and method Technical Field The invention relates to the technical field of medical equipment, in particular to an intelligent breathing machine humidifying device with a self-adaptive adjusting function and a method. Background The humidification of the breathing machine is a key link in mechanical ventilation support, and the key aim is to provide gas with proper temperature and humidity for patients so as to maintain the normal function of airway mucociliary and prevent the sticky or excessively thin sputum, thereby reducing the risks of complications such as airway injury, lung infection, airway obstruction and the like. The traditional humidifying technology mainly depends on preset fixed temperature or simple gear to perform constant output, and the humidifying process is an open loop system. The method ignores the influence of individual difference, dynamic evolution of illness state and fluctuation of environmental parameters of the patient, is difficult to realize accurate and personalized humidification treatment, and is easy to cause insufficient humidification or excessive humidification, thereby influencing the treatment effect and the comfort level of the patient. The breathing machine humidifying system comprises a breathing machine, a humidifier unit, a breathing pipe, a breathing mask and a control method of the breathing machine humidifying system, wherein the breathing machine actively configures and outputs compressed air flow, the humidifier unit is provided with a sterile sealed water tank and a micropore leakage pipe which is connected with the output end of the sealed water tank in a sealing mode, the breathing pipe is used for directionally conveying the humidified air flow, at least part of the micropore leakage pipe is arranged in the breathing pipe, the humidifier unit, the breathing machine and the breathing pipe are connected through a sealing joint, and the breathing mask is used for receiving the humidified air flow and is communicated with the output end of the breathing pipe. Most of traditional breathing machine humidification control is based on preset or simple feedback, synchronous sensing and depth fusion of multi-source information such as temperature and humidity at the near end of a patient airway, breathing waveform, environmental parameters and the like are lacked, and closed-loop self-adaptive adjustment in a true sense cannot be realized, so that design of an intelligent breathing machine humidification device with a self-adaptive adjustment function and a method for solving the problems are needed. Disclosure of Invention The invention aims to provide an intelligent breathing machine humidifying device with a self-adaptive adjusting function and a method thereof, which are used for solving the defects in the prior art. In order to achieve the above object, the present invention provides the following technical solutions: The utility model provides an intelligent breathing machine humidification device with self-adaptation regulatory function, includes breathing machine main part, humidification module sets up in the breathing machine main part, humidification module includes multisource perception module, preliminary treatment and calculation preview module, instant feedback and AI control module, power consumption calculation and regulation and control early warning module and humidification moisturizing module, wherein: The multi-source sensing module is used for collecting the temperature and humidity and the breathing waveform of the inhaled gas at the near end of the airway of the patient in real time; The multi-source sensing module is also used for detecting the water level of the humidification tank of the breathing machine, the temperature of the heating plate, the condensed water state of the pipeline and the temperature and humidity of the ward environment; The multi-source sensing module comprises a patient end sensing unit, a device end sensing unit and an environment end sensing unit, wherein: The patient end sensing unit comprises a miniature temperature and humidity sensor, a respiration waveform sensor and an end-expiration gas detection sensor, wherein: the miniature temperature and humidity sensor is integrated at the near end of the patient of the breathing machine pipeline and is used for monitoring the temperature and humidity of inhaled gas; The respiratory waveform sensor is used for collecting respiratory flow and pressure waveforms so as to identify airflow fluctuation and pressure rising characteristics caused by viscous sputum; the respiratory waveform sensor identifies waveform jitter characteristics caused by dry stimulus or cough; the end-tidal gas detection sensor is used for evaluating the water loss of the airway; The equipment end sensing unit comprises a humidifying tank water level sensor, a heating plate temperature sensor and an optical or weigh