Mechanical ventilation man-machine asynchronous data acquisition method, detection method and equipment thereof

Abstract

The invention provides a mechanical ventilation man-machine asynchronous data acquisition method, a mechanical ventilation man-machine asynchronous data detection method and mechanical ventilation man-machine asynchronous data detection equipment. The mechanical ventilation man-machine asynchronous data acquisition method comprises the following steps: starting and connecting a respirator and a simulated lung; setting a simulated breathing mode of the simulated lung through simulated lung control software according to a preset type of built-in case; adjusting the mechanical ventilation mode of the breathing machine to be not matched with the simulated breathing mode of the simulated lung, so that a man-machine asynchronous phenomenon is generated between the breathing machine and the simulated lung; and when the man-machine asynchronous phenomenon is stable, exporting related man-machine asynchronous data through the simulated lung control software. Through the above mode, the asynchronous data acquisition method provided by the invention can quickly and efficiently acquire different man-machine asynchronous data in a large amount and various types through the cooperation of the breathing machine and the simulated lung, and provides an important preposed basis for related teaching, research and application.

Description

technical field [0001] The present application relates to the technical field of medical detection, in particular to a method for acquiring human-machine asynchronous data of mechanical ventilation, a detection method and equipment thereof. Background technique [0002] Existing research on man-machine asynchronous detection of mechanical ventilation is mainly based on clinical data, which is difficult to obtain due to reasons such as patient privacy protection, and it is inconvenient to open access to mechanical ventilation data from different hospitals. These practical reasons hinder the acquisition of man-machine asynchronous data of mechanical ventilation, not to mention the acquisition of a large amount and rich variety of man-machine asynchronous data. In addition, the existing man-machine asynchronous detection algorithms generally seldom carry out sufficient multi-level correlation and characterization of the feature points in the input signal waveform, so there are ...

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Problems solved by technology

[0002] Existing research on man-machine asynchronous detection of mechanical ventilation is mainly based on clinical data, which is difficult to obtain due to the privacy protection of patients, and it is inconvenient to open access to mechanical ventilation data from different hospitals

These practical reasons hinder the acquisition of human-computer asynchronous data for mechanical ventilation, not to mention the acquisition of a large amount and variety of human-computer asynchronous data

In addition, the existing human-machine asynchronous detection algorithms generally seldom perform sufficient multi-level correlation and representation on the feature points in the input signal waveform, so there are certain improvements in the recognition validity and performance

[0003] At the same time, there are still relatively few technical introductions on the use of ventilators and simulated lungs to collect human-machine asynchronous data during mechanical ventilation.

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