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Epilepsia electroencephalogram signal classified detection device and method

A technology of classification detection and EEG signal, applied in the directions of diagnostic recording/measurement, medical science, sensors, etc., can solve the problem of low detection rate of EEG activity in epilepsy

Inactive Publication Date: 2012-05-02
SHANGHAI NORMAL UNIVERSITY
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Problems solved by technology

[0005] The purpose of the present invention is to disclose a device and method for classifying and detecting epileptic EEG signals to solve the problem that the detection rate of the existing detection devices and methods for epileptic EEG activity is not high

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  • Epilepsia electroencephalogram signal classified detection device and method
  • Epilepsia electroencephalogram signal classified detection device and method
  • Epilepsia electroencephalogram signal classified detection device and method

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Embodiment Construction

[0025] The device of the invention improves the detection rate of epileptic brain electricity by classifying and detecting epileptic brain electricity. figure 1 Examples of normal EEG and epileptic EEG signals.

[0026] The method for classification and detection of epilepsy EEG signals based on wavelet analysis and approximate entropy estimation realized by the device of the present invention is divided into three parts:

[0027] Perform wavelet analysis on collected normal EEG and epileptic EEG;

[0028] Perform approximate entropy calculation on each layer of detail signal after wavelet decomposition;

[0029] Classification detection using NEYMAN-PEARSON.

[0030] In the analysis of epileptic EEG, typical epileptic signals are divided into spike waves, sharp waves, spike-slow complexes, and sharp-slow complexes. Because they have different time-frequency characteristics, if the same detection standard is adopted without distinction, the optimal detection effect cannot b...

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Abstract

The invention discloses an epilepsia electroencephalogram signal classified detection device which comprises a module for carrying out small wave analysis on a normal electroencephalogram signal and an epilepsia electroencephalogram signal, a module for calculating approximate entropy of each layer of detailed signal obtained after small wave decomposition of the small wave analysis device, and a module for further carrying out classified detection utilizing a Neyman-Pearson criteria. According to the invention, various different types of epilepsia activities are distinguished from the obtained epilepsia signal by clinical data, electroencephalogram signal characteristics are extracted by a small wave analysis and approximate entropy combined mode, judgment and detection are carried out by the NEYMAN-PEARSON criteria, and as compared with the obtained result with unclassified detection result, the detection rate of the epilepsia electrical activity of brain is improved.

Description

technical field [0001] The invention belongs to the technical field of medical equipment, and in particular relates to a device and method for classifying and detecting epileptic EEG signals. Background technique [0002] Epilepsy is a chronic disease characterized by partial or entire brain dysfunction caused by abnormal discharge of neurons in the brain. The harm of epilepsy lies in the pain and physical and mental harm it brings to the patient, and even life-threatening in severe cases. If the patient is a child, it will also affect the physical and intellectual development. [0003] The most effective method of diagnosing patients with suspected epilepsy is an EEG, a noninvasive biophysical examination. The analysis of EEG signals is mainly to detect abnormal brain activities. The EEG of patients with epilepsy can usually record spike waves, sharp waves, and spike-and-slow complex waves. slow-wave complex) and sharp-and-slow-wave complex (sharp-and-slow-wave complex) a...

Claims

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Application Information

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IPC IPC(8): A61B5/0476
Inventor 汪春梅张崇明王丽慧
Owner SHANGHAI NORMAL UNIVERSITY
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