MUSE: A Portable Cost-efficient Lie Detector

The recent advanced in the low-cost, small-scale EEG scanners open the doors for many innovations in the domains of disease detection, social sciences, cyber security, and much more. In this paper, we investigate the possibility of using EEG signals as an indication of deception or lies. Further, we exploit one of the new EEG scanners, MUSE, to investigate its ability to provide what is needed to detect potential lies. Our experiments showed great success for the MUSE in providing what is needed for a moderate-quality lie detector, with very low-cost and complexity. Integrating machine-learning techniques into the presented results would provide a much more accurate detection opening the door for a vast number of potential applications.