Method and device for detecting lies on basis of electrodermal response and pupil change

Abstract

The invention discloses a method and a device for detecting lies on the basis of electrodermal response and pupil change. The method includes determining normal feature values of test persons according to normal electrodermal response data of the test persons in non-lying states, normal pupil data and preset weight values; determining test feature values of the test persons according to test electrodermal response data of the test persons in test states, test pupil data and the weight values; comparing the normal feature values to the test feature values to obtain lie detection results of the test persons. The method and the device have the advantages that the method and the device are high in feasibility, and high lie detection accuracy can be guaranteed.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of lie detection, and in particular to a lie detection method and device based on galvanic skin response and pupil changes. Background technique [0002] After more than half a century of development, polygraph technology has been widely used in the detection, security and security departments of Western countries led by the United States. The polygraph is an effective method for the public security department to identify criminal facts. It stimulates the testee by asking questions, so as to obtain the corresponding physiological changes of the testee. By analyzing these physiological changes, it is judged whether the testee is lie. Presently known polygraph mainly detects polygraphs by detecting physiological parameters such as galvanic skin response, chest respiration, pupil, and blood pressure. For example, when the subject is lying, he will feel nervous, which will cause the p...

AI Technical Summary

Problems solved by technology

[0004] Although the face recognition technology used in the above scheme is a hot topic and can be applied in many fields, it is not feasible to judge lying, because the facial expressions of each person will be quite different when lying. Some people will be expressionless when they lie, and some people will smile when they lie. Individual differences make the classification of data sets very difficult

And if a person smiles when they tell a lie, then a photo of a smile cannot tell whether the person is just smiling or lying

Therefore, the accuracy and feasibility of using facial expression recognition to determine whether a lie is low

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