Lie Detection Study Based on P300 and Extreme Learning Machine

Extreme learning machine (ELM) is a typical SLFN (single layer feedback network) and its efficiency has been proved by many literatures for pattern recognitions. In this paper, ELM is applied in lie detection for the first time in order to overcome the disadvantages of the current lie detection methods such as lower accuracy and slower training speed. ELM is used as a classifier to classify the guilty and innocent subjects. The experimental result is compared with support vector machine (SVM), artificial neural network (ANN) and fisher discrimination analysis (FDA). The comparison results show that the proposed method obtains the highest training and testing accuracy with the fastest training speed.