Human-machine asynchronization identification method and system, terminal and storage medium

The invention relates to a human-machine asynchronization identification method and system, a terminal and a storage medium. The method comprises the steps of obtaining breathing data in a current breathing period; dividing the breathing data into at least two sections of data with the same number of data points, respectively calculating the variance of each section of data, and taking a variance calculation result of each section of data as a characteristic value of the breathing data; and inputting the characteristic value into a trained breathing waveform classification model, classifying the breathing types of the breathing data through the breathing waveform classification model, and identifying a human-machine asynchronization phenomenon according to a breathing type classification result. According to the embodiment of the invention, the breathing data of each breathing period is segmented; and the human-machine asynchronization phenomenon is identified according to the classification result, the segme