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 multi-channel breathing data such as a simulated flow channel, a tidal volume channel, airway pressure, alveolar pressure, pleural cavity internal pressure, cardiac pressure and a current functional residual air volume channel under a man-machine asynchronous event simulated by a simulated lung and a breathing machine; performing variance, mean value, standard deviation, absolute value or square root feature extraction on the respiration data, generating sample data according to the extracted features, and training according to the sample data to obtain a 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, and the difference analysis of the respiration data of the adjacent channels is carried out by using the characteristics such as variance, mean value, standard deviation, absolute value or square root, so 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] When the breathing phase delivered by the ventilator does not match the breathing phase of the patient, there is a phenomenon of human-machine asynchrony between the patient and the ventilator. Human-machine asynchrony will have adverse effects on patients' treatment comfort, duration of mechanical ventilation, ICU stay time, and mortality. [0003] Among all modes of mechanical ventilation, the most prevalent asynchrony was futile inspiratory effort and double triggering. Ineffective inspiratory effort means that the trigger threshold of the ventilator is not reached after the inspiratory muscle is exerted, and no ventilator breath is produced, resulting in the patient's breathing rate being higher than the ventilator...

AI Technical Summary

Problems solved by technology

At present, the research data on machine asynchronous classification are all obtained through clinical practice, which takes a long cycle time, consumes a lot of labor time, and has many interference factors, which affect the classification accuracy.

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