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Academic Journal of Humanities & Social Sciences, 2021, 4(3); doi: 10.25236/AJHSS.2021.040303.

Research on non-invasive psychological detection technology based on artificial intelligence


Xinmeng Wang1, Yuanqing Shi2, Lu Liu2, *

Corresponding Author:
Lu Liu

1Nanjing Forest Police College, Nanjing, China

2Shenzhen Cmcross Technology Co., Ltd., Shenzhen, China

*Corresponding author: liu.lu@cmcross.cn


The studies on polygraph technology in China started in the 1990s, after nearly 30 years of research and practice, great progress has been made in technical methods, technical equipment, and the development of effective detection indicators, especially Multi-channel polygraph technology has been widely used in the fields of public security, prosecution, and law enforcement etc., with many successful use cases. But there are still many bottlenecks that are preventing the adaption of polygraph technology in the other areas. With the recent development of new technologies such as big data, machine vision and deep learning, new opportunities have been brought to solve historical issues. This article proposes a new psychological detection solution by leveraging these new technologies, specifically, we are proposing to use non-invasive technique, i.e., video based machine vision and deep learning, to measure the physiological indicator that cannot be controlled by subjective consciousness, which, combined with other indicators such as expression recognition, and big data, provides a better and more accurate multiple dimension psychological indicator recognition solution. This paper attempt to discuss the technical principles, system design, and application of this new solution.


non-invasive physiological index recognition, psychological recognition, emotion recognition, machine vision, deep learning, big data

Cite This Paper

Xinmeng Wang, Yuanqing Shi, Lu Liu. Research on non-invasive psychological detection technology based on artificial intelligence. Academic Journal of Humanities & Social Sciences (2021) Vol. 4, Issue 3: 10-16. https://doi.org/10.25236/AJHSS.2021.040303.


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