Lie detector system based on PhotoPlethysmoGraph (PPG) and Galvanic Skin Response (GSR) signals by means of neural network

The aim of this article is design a lie detector system using GSR and PPG. The data set was including of photoplethysmograph signals and galvanic skin response record through an inductive test and using classic polygraph device. Thenceforth, features of time and frequency were extracted. Consequently data were classified and accuracy sensitivity coefficients were calculated by applying these features to linear Discriminant analysis LDA, MLP and Elman neural networks. 20 people participated in the study. The mean age of participants was 36 years. Finally determination of lie was done with accuracy coefficient of 88% by applying Elman neural network. According to the findings in this study, the new method has introduced while offering a more comfortable recording and less diagnostic costs. This new method can be suggested for use as a lie screening system