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Magnetoencephalography epileptic spike wave recognition method and system

A recognition method and technology of epilepsy spines, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as energy-consuming, accuracy of classification results cannot be guaranteed, and judgment results are not the same

Active Publication Date: 2019-05-03
SICHUAN UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are many unfavorable factors in visual inspection. Generally, 60 minutes of data are recorded for one inspection. Finding spikes from very long data is very energy-consuming, which requires a high level of judgment by the analyst, and doctors have to contact with A large number of epilepsy cases, the accuracy of classification results cannot be guaranteed under heavy workload
Moreover, different experts judge the same record differently

Method used

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  • Magnetoencephalography epileptic spike wave recognition method and system
  • Magnetoencephalography epileptic spike wave recognition method and system
  • Magnetoencephalography epileptic spike wave recognition method and system

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Embodiment 1

[0058] Such as figure 1 As shown, the present invention proposes a method for identifying epileptic spikes in magnetoencephalography, comprising the following steps:

[0059] The MEG data and the nuclear magnetic resonance data of the epilepsy patient are collected, and the MEG data and the nuclear magnetic resonance data are fused to generate an MSI image, and the MEG data includes data with spikes and data without spikes.

[0060] In this step, the collected MEG data came from 20 patients diagnosed with insular lobe and insular opercular epilepsy who were examined by the Magnetoencephalography Center of Xuanwu Hospital of Capital Medical University. 9 females; aged 15 to 52 years, with an average of 28.7 years.

[0061] MRI should be performed at 1.5T or 3.0T for standard MRI scans, including SE sequence T1W1 and TSE sequence T2W1 in transverse position (slice thickness 5mm); oblique coronal view perpendicular to the long axis of the right hippocampus and liquid in transver...

Embodiment 2

[0100] Such as image 3 As shown, corresponding to Embodiment 1, this embodiment provides a MEG epilepsy spike recognition system, including:

[0101] The data acquisition unit is used to collect MEG data and nuclear magnetic resonance data of epilepsy patients, and fuse the MEG data and nuclear magnetic resonance data to generate MSI images, and the MEG data includes spike data and spike-free data;

[0102] A preprocessing unit, configured to preprocess the MEG data to obtain N spike data segments and spike-free data segments of the same duration respectively;

[0103] A feature extraction unit is used to extract the feature vectors of each section of data from the generated MSI image to form a sample data set, and divide the sample data set into a training set and a test set;

[0104] A training model unit, configured to use the training set and labels to train the classifier to obtain a trained classifier model;

[0105] The epileptic spike identification unit is used to ...

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Abstract

The invention relates to a magnetoencephalography epileptic spike wave recognition method and system. The method comprises the following steps of dividing MEG data into spike wave data and non-spike wave data, and pretreating the MEG data to respectively obtain the spike wave data and the non-spike wave data, of which the N segment phases are the same in length; performing analytical treatment onthe obtained segments of data, performing extraction to obtain characteristic vectors of various segments of data to form a sample dataset, and dividing the sample dataset into a training set and a test set; training a radial primary kernel function support vector machine classifier through the training set to obtain a trained classifier model; and inputting the test set to the classifier model torecognize whether epileptic spike waves exist or not. Automatic recognition of epilepsy brain magnetic signals can timely judge the condition of the patients, wherein the judgment accuracy rate can achieve 93.8%, the labor intensity of doctors is reduced, the detection accuracy rate is increased, and the omission factor and the false positive rate are reduced. The magnetoencephalography epilepticspike wave recognition method and system have important significance clinically.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a method and system for identifying epileptic spikes in magnetoencephalography. Background technique [0002] The main manifestations of epilepsy in the magnetoencephalogram are spikes and sharp waves, which are sometimes not distinguished and are collectively referred to as epileptic transients or spikes. Spikes and sharp waves stand out from the background activity, with a higher amplitude and a period between 20ms and 200ms. [0003] The analysis of magnetic brain signals is mainly the detection and analysis of abnormal brain activities. These tasks are currently done by medical workers through visual detection of patients' magnetoencephalograms based on experience. There are many unfavorable factors in visual inspection. Generally, 60 minutes of data are recorded for one inspection. Finding spikes from very long data is very energy-consuming, which requires a high level of ju...

Claims

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Application Information

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IPC IPC(8): A61B5/055A61B5/00
Inventor 张军鹏张航宇刘凯
Owner SICHUAN UNIV
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