Symbolized permutation transfer entropy-based epileptic electroencephalogram bidirectional coupling analysis method

A two-way coupling and analysis method technology, applied in the fields of sensors, medical science, complex mathematical operations, etc., can solve the problem of fewer brain channels

Active Publication Date: 2021-01-22
HANGZHOU DIANZI UNIV
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Problems solved by technology

At present, there are few literatures on the synchronization and correlation between brain channels in patients with epilepsy, and further research and analysis are needed

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  • Symbolized permutation transfer entropy-based epileptic electroencephalogram bidirectional coupling analysis method
  • Symbolized permutation transfer entropy-based epileptic electroencephalogram bidirectional coupling analysis method
  • Symbolized permutation transfer entropy-based epileptic electroencephalogram bidirectional coupling analysis method

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Embodiment Construction

[0052]In order to better analyze the coupling strength of multi-channel EEG and the synchronization strength of brain intervals, the present invention mainly improves the analysis method of EEG. The present invention proposes to use multi-scale symbolization to symbolize the original EEG EEG signal, and then use the arrangement mode to reconstruct the sequence to obtain a new time sequence, and use the transfer entropy algorithm to calculate the two-way coupling strength between EEGs for the reconstructed sequence. Finally, the multi-channel EEG was divided into four brain regions, and the bidirectional synchrony was extended to multi-channel synchronicity analysis by using the S estimator to explore the synchronization strength between brain regions.

[0053] The specific flow chart of the two-way coupling analysis method of epileptic EEG based on symbolized permutation transfer entropy is as follows: figure 1 As shown, the present invention proposes a multi-scale symbolic p...

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Abstract

The invention discloses a symbolized permutation transfer entropy-based epileptic electroencephalogram bidirectional coupling analysis method. The epileptic electroencephalogram bidirectional couplinganalysis method comprises the following specific steps of firstly extracting coupling features of multi-channel epileptic electroencephalogram signals by adopting a method of multi-scale symbolized permutation transfer entropy, and selecting a proper scale and frequency band to construct an electroencephalogram synchronous matrix; and secondly, screening important channels during epileptic seizure based on a significance analysis method, and performing inter-channel bidirectional coupling analysis. In order to further research the overall synchronous relationship of the whole cerebral cortexarea, the multi-channel electroencephalogram signals are divided into 4 brain areas by the epileptic electroencephalogram bidirectional coupling analysis method, and synchronism analysis of multi-channel electroencephalogram signals is performed by using an S estimator under frequency bands of delta, theta, alpha and beta. The epileptic electroencephalogram bidirectional coupling analysis method improves the features of bidirectional coupling and synchronism of the epileptic electroencephalogram signals, and a more scientific and reasonable analysis method is made.

Description

technical field [0001] The invention relates to a method for analyzing the two-way coupling and synchronization strength of epileptic EEG signals by using multi-scale symbolic permutation transfer entropy, especially the location of epileptic seizures based on multi-channel EEG signals of epileptic patients, which belongs to the technical field of intelligent pattern recognition. Background technique [0002] Epilepsy is a chronic disease of sudden and recurrent brain dysfunction. Due to the different starting sites and transmission methods of abnormal electrical activity in the brain, the clinical manifestations of epilepsy are complex and diverse, including transient sensory disturbances, limb twitches, loss of consciousness, behavioral disturbances, etc. , causing serious physical and mental damage to the patient. EEG signals contain important information about brain activity, and the location, diagnosis and treatment of epileptic seizures based on EEG signals have been p...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/369A61B5/372A61B5/00G06F17/18
CPCA61B5/4094A61B5/7203A61B5/7235G06F17/18
Inventor 高云园高博王翔坤朱涛张卷卷郑敏杰
Owner HANGZHOU DIANZI UNIV
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