title: A novel approach for lie detection based on F-score and extreme learning machine.
abstract: A new machine learning method referred to as F-score_ELM was proposed to classify the lying and truth-telling using the electroencephalogram (EEG) signals from 28 guilty and innocent subjects. Thirty-one features were extracted from the probe responses from these subjects. Then, a recently-developed classifier called extreme learning machine (ELM) was combined with F-score, a simple but effective feature selection method, to jointly optimize the number of the hidden nodes of ELM and the feature subset by a grid-searching training procedure. The method was compared to two classification models combining principal component analysis with back-propagation network and support vector machine classifiers. We thoroughly assessed the performance of these classification models including the training and testing time, sensitivity and specificity from the training and testing sets, as well as network size. The experimental results showed that the number of the hidden nodes can be effectively optimized by the proposed method. Also, F-score_ELM obtained the best classification accuracy and required the shortest training and testing time.
authors.affiliation: College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, People's Republic of China.
authors.forename: Junfeng
authors.initials: J
authors.lastname: Gao
authors.forename: Zhao
authors.initials: Z
authors.lastname: Wang
authors.forename: Yong
authors.initials: Y
authors.lastname: Yang
authors.forename: Wenjia
authors.initials: W
authors.lastname: Zhang
authors.forename: Chunyi
authors.initials: C
authors.lastname: Tao
authors.forename: Jinan
authors.initials: J
authors.lastname: Guan
authors.forename: Nini
authors.initials: N
authors.lastname: Rao
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004569:Electroencephalography; D005260:Female; D006167:Guilt; D006801:Humans; D008014:Lie Detection; D008297:Male; D008962:Models, Theoretical; D025341:Principal Component Analysis; D055815:Young Adult