Techniques for Behavior Lie Detection with the Aid of Physiological Signals: A Review

Emotional intelligence is an extremely valued aspect of intelligence therefore; machine intelligence needs to encompass emotional intelligence. Intensive research has been carried out in this field to enable machines to understand emotional states of human. Non-verbal communication is major mode of expression among humans and it constitutes of gestures, facial expressions etc. Facial expressions can be deceptive and a person might fake his/her emotional state by the usage of facial expressions. Physiological signals can be used in conjunction with facial expressions to detect a behavioral lie. It is of prime importance to automate this task. In this paper, we survey various techniques which make use of machine learning and physiological signals for detection of behavior lie. Identification of robust physiological signals yielding accurate results which aid in in the identification of emotional state of an individual. Survey also aims at identification of combination of the type of physiological signal and the classification algorithm used for classification of the emotion.

Keywords: Machine learning, Behavior detection, Physiological sensors, Face recognition

Suggested Citation: Suggested Citation

Pandey, Payal and Thakur, Divyansh and Thakur, Bishan, Techniques for Behavior Lie Detection with the Aid of Physiological Signals: A Review (April 11, 2020). Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence (ICAEEC) 2019, Available at SSRN: https://ssrn.com/abstract=3573551 or http://dx.doi.org/10.2139/ssrn.3573551