Mechanical ventilation man-machine asynchronous detection and recognition method based on attention mechanism

Abstract

The invention relates to the technical field of intelligent control of medical instruments, in particular to a mechanical ventilation man-machine asynchronous detection and recognition method based on an attention mechanism. According to the method, a kernel-level attention module and a time sequence attention module are constructed respectively in sequence, signal feature segments which are more beneficial to different man-machine asynchronous types can be found from the convolution kernel feature level of waveform data and the time sequence level of signals, higher attention is given to the feature segments, and therefore, man-machine asynchronization can be better distinguished.

Description

technical field [0001] The invention relates to the technical field of intelligent control of medical equipment, in particular to an attention mechanism-based human-machine asynchronous detection and recognition method for mechanical ventilation. Background technique [0002] The ventilator is an important life device based on respiratory function support. It is widely used in the intensive care department and general department of the hospital. Some ventilators have also entered the family and become some auxiliary household devices for daily sleep. Provides vital support for those with respiratory impairments. [0003] Generally speaking, one of the most important functions of a ventilator is its ventilation sensitivity, whether it can provide the same frequency of air supply / ventilation support when the patient or user needs to inhale, and whether the same can be timely when the patient exhales. Make the corresponding switch and decompose it, that is, the ventilator must...

AI Technical Summary

Problems solved by technology

[0004] When the breathing demand of the patient is not synchronized with the gas supply switching action of the ventilator, the airflow velocity (Flow), airway pressure (Paw), and ventilation capacity (Volume) in the pipeline will show a certain pattern, and these patterns have certain characteristics. The law can be detected manually or by algorithms, but manual detection takes a lot of time and requires relevant training in advance, and the labor cost is relatively expensive, especially for my country's high-quality medical resources; vigorously develop artificial intelligence-based Man-machine asynchronous detection algorithm, necessary and important

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