Scalp electroencephalogram (EEG) retrospective epileptic seizure point detection method and system

A technology of EEG signals and epileptic seizures, applied in diagnostic recording/measurement, medical science, complex mathematical operations, etc., can solve problems such as inconvenient analysis, high misjudgment rate, crosstalk between EEG signals, etc., and achieves significant optimization effects, The effect of remarkable effect and good wide adaptability

CN105249962AInactive Publication Date: 2016-01-20BEIJING UNION UNIVERSITY
5 Cites 8 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2016-01-20
Estimated Expiration
Not applicable · inactive patent

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention belongs to the technical field of scalp electroencephalogram (EEG), and presents a scalp EEG retrospective epileptic seizure point detection method and system. The method is as follows: retrospective analysis is carried out on EEGs with various artifact EEGs being removed through a non-linear dynamics sample entropy threshold value detection method to determine the epileptic seizure point. The scalp EEG retrospective epileptic seizure point detection system includes an EEG receiving module, an epileptic seizure point determining module, and an information output module, wherein the EEG receiving module is used for receiving original EEG collected clinically; the epileptic seizure point determining module is used for analyzing and determining the retrospective epileptic seizure point through the EEG received by the EEG receiving module; the information output module is used for outputting the retrospective epileptic seizure point determined by the epileptic seizure point determining module. According to the scalp EEG retrospective epileptic seizure point detection method and system, the EEG data can be demixed in 10s, so that the epileptic seizure point can be quickly determined and the effect is obvious.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the technical field of scalp electroencephalogram signals, in particular to a method and system for retrospectively detecting epileptic seizure points of scalp electroencephalogram signals. Background technique

[0002] Epilepsy is a disease of nervous system disorder. According to literature reports, the incidence of the disease in the population is about 0.5% to 2%. It is characterized by disorder and brings great inconvenience to the lives of patients. Electroencephalogram (EEG) examination is a common technique for epilepsy diagnosis and focus location in clinical practice at present, and the analysis of epilepsy by EEG is easily accepted by doctors and patients. The time resolution of the EEG signal is high, and it can accurately reflect the time-varying characteristics of the brain at the millisecond level. The 24-hour long-range EEG signal is an important basis for the diagnosis of epilepsy. However, in the face of suc...

Examples

Embodiment Construction

[0044] The present invention will be described in further detail below in conjunction with the accompanying drawings. It is necessary to point out that the following specific embodiments are only used to further illustrate the present invention, and should not be construed as limiting the protection scope of the present invention. SUMMARY OF THE INVENTION Some non-essential improvements and adjustments are made to the present invention.

[0045] like figure 1 As shown, the scalp EEG signal retrospective epileptic seizure point detection method of the present invention comprises the following steps:

[0046] Step 1. Obtain and remove various artifact EEG signals

[0047] Realize fast blind source separation and remove EEG signals through negative entropy of EEG signals and two-stage genetic optimization algorithm

[0048] Various artifacts, especially the influence of ECG noise. The blind source fast separation algorithm can be roughly described as:

[0049] S-->mixing matr...