N400 evoked potential lie detection method based on sample entropy

Abstract

The invention provides an N400 evoked potential lie detection method based on sample entropy. The method comprises the following steps of extracting and synchronously amplifying electroencephalogram, collecting the electroencephalogram, receiving and synchronously storing the electroencephalogram, preprocessing the electroencephalogram, conducting superposition averaging on the electroencephalogram, extracting an electroencephalogram sample entropy feature value, conducting state judgment on whether a lie is told or not, measuring the complexity of the N400 induced electroencephalogram on the basis of the sample entropy, reflecting nonlinear features of the electroencephalogram, finding a feature threshold value for distinguishing whether a lie is told or not through statistical analysis of data, comparing the threshold value with an absolute value of the entropy gradient of probe stimulus and indifferent stimulus ERP electroencephalogram data samples, and judging whether a lie is told or not. The defects existing when lie testing judgment is performed by means of evoked potential waveform geometric properties in the prior art are overcome, so that the method has the advantage that the stable lie recognition accuracy can be effectively ensured.

Description

technical field [0001] The invention belongs to the combined application of the field of cognitive neuroscience and the field of information technology, and relates to a lie detection method of event-related potential N400, in particular to a lie detection method of N400 evoked potential based on sample entropy. Background technique [0002] As a psychological phenomenon, lying does not only appear in today's society. From the historical archives we know so far, we can see that lying existed in the early days of human society. Although many lies are well-intentioned, there are also many lies that endanger national security, social security, and fairness and justice. For example, in espionage crimes, job crimes and criminal investigations, criminals lie deliberately 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 the crime. Therefore, how to identify lies accurat...

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.

Images