Breathing machine man-machine asynchronous classification method, terminal and storage medium

Abstract

The invention relates to a breathing machine man-machine asynchronous classification method and system, a terminal and a storage medium. The method comprises the steps: collecting the multi-channel breathing data of a simulated flow channel, a tidal volume channel, airway pressure, alveolar pressure, pleural cavity internal pressure, cardiac pressure, a corrugated pipe position channel and the like under a man-machine asynchronous event simulated by a simulated lung and a breathing machine; carrying out replacement deviation index (PDI) feature extraction on the respiration data, and labeling the respiration data according to the extracted PDI features; inputting the labeled respiration data into a network model for training to obtain a trained man-machine asynchronous classification model; and classifying the breathing machine man-machine asynchronous events through the trained man-machine asynchronous classification model. According to the embodiment of the invention, the acquired respiration data is small in interference and convenient to acquire, difference analysis of the respiration data of the adjacent channels is carried out by using the PDI features, and the accuracy of man-machine asynchronous classification is improved.

Description

technical field [0001] The invention belongs to the technical field of medical data processing, and in particular relates to a human-machine asynchronous classification method, system, terminal and storage medium of a ventilator. Background technique [0002] Mechanical ventilation is the use of mechanical force to generate or enhance the patient's respiratory function with the help of a ventilator. In critically ill patients, mechanical ventilation aims to improve oxygenation and reduce the patient's work of breathing and the load on the respiratory muscles to support the patient's improvement. During treatment, in order to meet the needs of the patient, the inspiratory time and tidal volume of the ventilator must match the inspiratory time and tidal volume of the patient. However, in practical applications, mechanical ventilation cannot adapt to different conditions of patients due to improper setting of ventilator parameters. Asynchronous (not synchronous) phenomena. ...

AI Technical Summary

Problems solved by technology

[0008] At present, the automatic alarm system is used to provide early warning for the asynchronous event of the ventilator. However, the existing automatic alarm system usually relies on simple thresholds, resulting in frequent false positives and causing great disturbance to medical staff.

In addition, the current data collection method for human-machine asynchronous research is to artificially remove noise interference after clinical collection. The data collection takes a long period of time and events, and human identification of interference factors is large, which will affect the accuracy of the data.

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