N400 evoked potential lie detection method based on sample entropy

Abstract

The invention provides a N400 evoked potential lie detection method based on sample entropy, comprising the following steps: EEG signal extraction and synchronous amplification; EEG signal acquisition; EEG signal reception and synchronous storage; EEG signal preprocessing; EEG signal Superposition average; EEG signal sample entropy feature value extraction; lying or not state judgment, combined with sample entropy to measure the complexity of N400-induced EEG signals, reflecting its nonlinear characteristics, and finding the characteristics that distinguish lying or not through statistical analysis of data The threshold value compares the absolute value of the entropy value difference between the probe stimulus and the irrelevant stimulus ERP EEG signal data sample with the size of the threshold value, and judges whether to lie. The invention has the advantage of effectively ensuring a stable lie recognition accuracy rate.

Description

Technical field [0001] The present invention belongs to the combined application of the field of cognitive neuroscience and the field of information technology, and relates to a polygraph method for event-related potential N400, specifically a polygraph method for N400 evoked potential based on sample entropy. Background technique [0002] As a psychological phenomenon, lying does not only appear in today's society. It can be seen from the historical archives that we currently know that lying occurred in the early days of human society. Although many lies are well-intentioned, there are also many lies that endanger national security, social security, fairness and justice. For example, in espionage crimes, duty crimes, and criminal investigations, criminals deliberately lie in order to conceal crimes and evade legal sanctions. During the trial of a case, lies will have a huge impact on the trial of the case and the determination of crime. Therefore, how to accurately and effecti...

AI Technical Summary

Problems solved by technology

Although these lie detection studies have achieved certain results, their lie recognition is mainly based on the analysis of the geometric properties of the evoked potential waveform (amplitude, wave area, peak-to-peak value, etc.), but the geometric properties cannot effectively reflect the EEG signal. Features, this method of lie detection is not satisfactory, the effect of lie detection is not ideal and stable

Moreover, the P300-based lie detection cannot rule out the influence of small-probability stimuli on lie detection, because in previous ERP studies, the presentation of small-probability stimuli can induce significant P300, and the presentation of case-related "probing stimuli" can also induce P300.

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