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Epileptic seizure prediction system and method

A technology for epileptic seizures and prediction systems, applied in diagnostic recording/measurement, medical science, diagnostic signal processing, etc., can solve the problems of amplifying the influence of proportional noise on the model, emphasizing proportional data, discarding, etc., to solve the problem of sample imbalance, The effect of improving prediction accuracy

Pending Publication Date: 2021-11-09
SHANDONG INST OF ADVANCED TECH CHINESE ACAD OF SCI CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Among them, the downsampling process will discard a large amount of valid data, and there is an overfitting problem; oversampling does not actually introduce more data to the model, and overemphasizes the proportional data, which will amplify the impact of proportional noise on the model

Method used

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  • Epileptic seizure prediction system and method
  • Epileptic seizure prediction system and method
  • Epileptic seizure prediction system and method

Examples

Experimental program
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Embodiment 1

[0098] Such as figure 1 As shown, this embodiment provides a system for predicting epileptic seizures, which specifically includes:

[0099] The EEG signal acquisition module is used to collect EEG signals of epilepsy patients to obtain EEG signals of different frequencies;

[0100] The EEG signal segmentation module is used to segment the EEG signals of different frequencies according to the epileptic seizure stage to obtain the a-segment EEG signal;

[0101] The feature information extraction module is used to extract the features of the a-segment EEG signal respectively, and obtain the feature matrix of each segment of the EEG signal;

[0102] A feature filter processing module, configured to filter the feature matrix of each segment of the EEG signal to obtain a group of data samples;

[0103] The feature matrix generation module is used to generate the feature matrix of the epilepsy patient's EEG signal using the generative confrontation network, and use the feature mat...

Embodiment 2

[0167] Such as Figure 4 The present embodiment shown provides a method for predicting epileptic seizures applied to the system provided in Embodiment 1, which specifically includes:

[0168] S1: Collect the EEG signals of epilepsy patients to obtain EEG signals of different frequencies.

[0169] S2: Segment the EEG signals of different frequencies according to the stages of the epileptic seizures to obtain segment a EEG signals. Wherein, the operation steps of obtaining the segment a EEG signal specifically include:

[0170] Determine whether the frequency of the EEG signal of the epilepsy patient is in the interval between seizures, and if so, divide the EEG signal into X 1 part;

[0171] Determine whether the frequency of the EEG signal of the epilepsy patient is in the pre-seizure stage, and if so, divide the EEG signal into X 2 part;

[0172] Determine whether the frequency of the EEG signal of the epilepsy patient is in the epileptic seizure period, and if so, divid...

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Abstract

The invention relates to an epileptic seizure prediction system and method, and belongs to the technical field of epilepsy seizure prediction. The epileptic seizure prediction system comprises an electroencephalogram signal acquisition module, an electroencephalogram signal segmentation module, a feature information extraction module, a feature filtering processing module, a feature matrix generation module and an epileptic seizure prediction module. According to the epileptic seizure prediction system, the electroencephalogram feature information of the epileptic in the epileptic seizure period is generated through the generative adversarial network of the feature matrix generation module, so that the prediction precision of the epileptic seizure of the epileptic is improved.

Description

technical field [0001] The present invention relates to the technical field of epileptic seizure prediction, in particular to a system and method for epileptic seizure prediction. Background technique [0002] Epilepsy is the second most common brain disorder after cerebrovascular disease, affecting more than 0.5% of people worldwide. According to the data released by the Ministry of Health, the total number of epilepsy patients in the country is about 8 million, and the number of new patients exceeds 350,000 every year. Among the patients, people under the age of 18 account for 75%-80%. Epilepsy is a chronic neurological disorder caused by abnormal discharge of neurons in the brain. During a seizure, a person experiences sudden seizures, convulsions, or loss of consciousness. Moreover, the time and location of epilepsy attacks are not subject to human control, which makes epilepsy patients not only unable to protect their own life safety, but also affects the personal saf...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/369
CPCA61B5/4094A61B5/369A61B5/72A61B5/7264
Inventor 陈财张昔坤李文超彭福来王星维韩玉杰王琳李光林
Owner SHANDONG INST OF ADVANCED TECH CHINESE ACAD OF SCI CO LTD
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