A method, device and equipment for identifying sleep staging events

Abstract

This application discloses a method for identifying sleep staging events, which is applied to the interpretation of sleep EEG mixed signals, including dividing sleep EEG mixed signals at preset time intervals, and obtaining a preset number of mixed signal segments; using each The mixed signal segment obtains the time domain waveform corresponding to each mixed signal segment; uses the preset rules in the rule library to process each time domain waveform to obtain the processing result; if the processing result meets the screening requirements corresponding to the preset rule, then the processing result corresponds to Mixed-signal segments are labeled with sleep staging event categories corresponding to preset rules. This identification method effectively avoids the huge difference brought by the pure frequency band parameters to different individual users, and further improves the accuracy of interpreting the sleep EEG mixed signal. The present application also discloses a sleep staging event recognition device, equipment and computer-readable storage medium, all of which have the above beneficial effects.

Description

technical field [0001] The present application relates to the field of sleep staging interpretation, in particular to a sleep staging event recognition method, and also to a sleep staging event recognition device, equipment, and computer-readable storage medium. Background technique [0002] The phenomenon of sleep disorders has become an important problem that endangers public health. Establishing a standard and systematic method to define the nature of sleep and related events is of great significance to the foundation of sleep medicine. The existing sleep stage interpretation method can be used to analyze the phenomenon of sleep disorders. The method collects and processes the epoch of the sleep EEG mixed signal segment, obtains the corresponding processing result, and realizes the analysis of the above-mentioned sleep disorder phenomenon according to the processing result. [0003] In order to ensure the accuracy of the sleep staging interpretation result, the result wi...

AI Technical Summary

Problems solved by technology

However, because sleep staging events mostly belong to pure frequency band parameters, such as α wave, β wave, etc., there will be great differences for different individual users, so there will be great deviations in the judgment results of different users, that is, the algorithm is widely used. The conversion rate is low, which further reduces the accuracy of sleep EEG mixed signal interpretation results.

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