LieWaves: dataset for lie detection based on EEG signals and wavelets

Published: 12 February 2024| Version 2 | DOI: 10.17632/5gzxb2bzs2.2
Musa Aslan,


This dataset includes EEG signals for lie detection. EEG signals were collected using a wearable and portable EEG device called Emotiv Insight, which has 5 channels, from 27 different subjects. The subjects participated in two experiments, taking on the roles of deceivers and truth-tellers. In each experiment, a box with 5 different beads was given to the subjects, and they were instructed to take 2 beads from the box and place them in their pockets. In the first experiment, subjects were asked to decide whether to assume the role of a deceiver or a truth-teller. In the second experiment, they were required to take on the opposite role. During the experiments, subjects watched a video composed of images of the beads in the box placed in front of them. The video clip started with a 3-second black screen, followed by 2 seconds of bead images and 1 second of a black screen, repeating in this pattern. After obtaining EEG data, the initial 2 seconds of excessive signal data were removed from the raw data, resulting in a total of 75 seconds of EEG data. In the deceiver role, subjects clicked the button in their left hand labeled "no" if the displayed image matched the bead they took, and the button in their right hand labeled "yes" if it did not, thus deceiving about all the images. For the truth-teller role, the opposite actions were taken, clicking "yes" for the taken bead image and "no" for the not-taken bead image, thus telling the truth for all images. EEG signals were recorded following this procedure. The EEG signals underwent an offset removal process to obtain raw EEG data. Both raw data and preprocessed EEG data were stored in .csv format. The purpose of this dataset is to provide EEG signals for lie detection, offering an alternative and diverse dataset with different channel counts. When this data set is used, the relevant article must be cited. The relevant article citation is below. Aslan, M., Baykara, M. & Alakus, T.B. LieWaves: dataset for lie detection based on EEG signals and wavelets. Med Biol Eng Comput (2024).


Steps to reproduce

Signal Type: EEG signals (Time series) Purpose of Use: Lie Detection Used Device: Emotiv Insight Number of Channels: 5 Number of Subjects: 27 Number of Experiments: 2 Number of Samples: 9600 Stimulus Type Image


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