Brain wave medical record signal reduction method based on three-level cross-game energy tree

Abstract

The invention discloses a method for reducing brain wave medical record signals based on a three-layer cross game energy tree. In this method, two adjacent three-layer cross-game energy trees Ti and Tj are firstly designed, and the selfish game is realized in the same main layer and the cross-cooperative game is realized between different main layers. The depth-first search strategy is used to select the two game energy trees. The global optimal elites Elitisti_c and Elitistj_c; then assign the elite energy gain matrix PMENn×n to the optimal elites, and enhance the elites to obtain adaptive Nash energy exploration and development balance performance in the main layer; finally realize the cross-game energy reduction of brainwave medical record signals , so that the optimal elite converges to the optimal Nash equilibrium point of each main layer under the drive of the elite energy vector Γ, and achieves the balance of the reduction accuracy of the brainwave medical record signal, thereby outputting the global optimal brainwave medical record signal. The invention can effectively improve the reduction efficiency of brainwave medical record signals, provide important methods for brainwave signal noise elimination, feature extraction and analysis, etc., and has strong application value for brain disease diagnosis and auxiliary treatment.

Description

Technical field: [0001] The invention relates to the field of biomedicine, in particular to a method for reducing brain wave medical record signals based on a three-layer cross game energy tree. Background technique: [0002] The brain wave signal in the electronic medical record is a waveform with a potential of about millivolts on the cerebral cortex under the scalp detected by medical instruments. The brain wave signal is divided into δ wave, θ wave, α wave, β wave and γ wave according to its frequency. waves, where delta and theta waves are slow waves, and beta and gamma waves are fast waves. Brain wave signals have a certain regularity. When there is a lesion in the brain, especially in the cortex, the regularity of the brain wave is destroyed, which will cause abnormal brain waves, and the waveform will change. The analysis of the brain wave medical record signals can effectively assist clinical brain waves. Disease diagnosis. However, since the brain wave signal wav...

AI Technical Summary

Problems solved by technology

[0003] At present, Fourier transform, frequency domain energy analysis, wavelet transform, fast independent component analysis and other methods are generally used to improve the shortcomings of brain wave medical record signals such as uncertainty, timeliness, weakness, diversity and nonlinearity, but the brain wave medical records obtained by these methods The signal prevents a lot of information from the original brainwave signal from being retained, and it is very likely that the useful brainwave signal will be suppressed or processed as noise, which indirectly changes the characteristics of the brainwave signal, making it impossible for us to determine the frequency of the brainwave in the electronic medical record system. , amplitude, quantity, location, appearance, pathological waves, etc. for effective analysis

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