Method for classifying sleep stages on basis of sleep EGG (electroencephalogram) signal detection

Abstract

The invention relates to the field of identification of sleep EGG (electroencephalogram) detection signals and discloses a method for classifying sleep stages on basis of sleep EGG (electroencephalogram) signal detection. The method comprises steps as follows: (1), signal acquisition equipment is connected with a left frontal pole and a right frontal pole and is used for acquiring EGG signals, electrooculogram signals and lower jaw electromyographic signals; (2), filtering is performed, the signals are subjected to filtering processing through a low pass filter, and the signals with frequency higher than 50 Hz are cut off, and the signals with frequency lower than 50 Hz are allowed to pass; (3), the signals are subjected to frequency band division, and a time domain is subjected to band division processing with 30s as a unit; (4), characteristic values are extracted, energy of each frequency band is calculated, and an energy ratio is taken as a characteristic value of each frequency band. According to the method, a polysomnography is simplified through the acquisition equipment, then the acquired signals are processed, and the signals of the frequency bands are separated, so that which sleep stage a detected person is in is determined; the overall process is simple to operate, the analysis is automated, and the problem of insufficiency of equipment in a hospital can be effectively solved.

Description

technical field [0001] The invention relates to the field of recognition of sleep electroencephalogram detection signals, in particular to a method for classifying sleep stages based on detecting sleep electroencephalogram signals. Background technique [0002] Brain waves are formed by the spontaneous, rhythmic and comprehensive electrical activities of a large number of neurons under the cerebral cortex. Since 1924, when German neuroscientists first recorded and described human brain activity, the EEG has opened up the significance of the era of modernization. Since brain waves play an important role in the diagnosis of epilepsy, tumors and other mental diseases, the detection and analysis of brain waves and the extraction of features have great research value. [0003] Polysomnography can accurately measure and record human brain electrical activity by placing electrodes on multiple points of the brain. The polysomnography is a multi-channel medical device with complex ...

AI Technical Summary

Problems solved by technology

[0004] The present invention aims at the disadvantages of cumbersome brain electrical activity measurement, complex lead methods, and inability to process EEG data quickly and accurately in the prior art, and provides a brain electrical activity measurement that is simple, simple lead methods, and EEG data that can be quickly and accurately processed. Accurate processing method for classifying sleep stages based on detecting sleep EEG signals

Images