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Polygraph method based on multi-channel EEG signal margin factor

An EEG signal and margin technology, which is applied in diagnostic recording/measurement, medical science, diagnosis, etc., can solve the problems of large amount of stimulation and low accuracy of polygraph detection technology, so as to improve the accuracy of polygraph detection and reduce the number of stimulations Effect

Active Publication Date: 2019-09-03
SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a method for detecting polygraphs based on margin factors of multi-lead EEG signals, which is intended to solve the problems of large amount of stimulation and low accuracy in the existing ERP-based polygraph technology

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  • Polygraph method based on multi-channel EEG signal margin factor
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  • Polygraph method based on multi-channel EEG signal margin factor

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Embodiment Construction

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0027] Such as figure 1 and figure 2 As shown, the embodiment of the present invention provides a method for detecting polygraphs based on margin factors of multi-conductor EEG signals, comprising the following steps:

[0028] Step S1, EEG signal collection and preprocessing: Probe and stimulate two types of subjects, honest and lying, and collect EEG signals from multiple parts of the head of the two types of subjects in real time through multi-conductor EE...

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Abstract

The invention provides a polygraph method based on a multi-channel EEG signal margin factor. The method comprises the following steps: performing real-time collecting on the EEG signals of multiple parts of the heads of both honest and lying subjects through a multi-channel EEG electrode, and performing pre-processing on the collected EEG signals; calculating the margin factor for each of the EEGdata, and extracting the margin factor of the electrode having significant differences between the two types of subjects as a classification feature; using the margin factor index of the electrodes with significant differences between the two types of subjects, constructing a feature vector as the sample data, and verifying an initial machine learning classifier model by the sample data to obtainthe classifier with a best parameter combination; and performing lie detection on the tester by the classifier. The method for calculating the margin factor of the multi-channel EEG signal is appliedto the field of EEG lie detection, can well distinguish the EEG signals of the honest and lying groups, and achieves the purposes of detecting lies and improving the lie detection efficiency and accuracy.

Description

technical field [0001] The invention relates to the field of electroencephalogram lie detection, in particular to a lie detection method based on multi-conductor electroencephalogram signal margin factors. Background technique [0002] Lying is a common social and psychological phenomenon in human society. Lies have become a factor affecting social stability and unity, and pose a serious threat to the property and life safety of the people. Therefore, psychophysiologists and other related experts have been working hard to find effective lie detection methods. The effectiveness of lie detection has been confirmed in long-term and extensive application practice at home and abroad. First of all, polygraph technology has important application value for the detection of criminal investigation cases. In addition, lie recognition is also of great significance to the treatment of mental illness and mental disorders. In addition, the current international anti-terrorism situation...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/16A61B5/0476A61B5/0478
CPCA61B5/164A61B5/291A61B5/369
Inventor 田洪君高军峰龚佳奇
Owner SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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