A Microcontroller-based Lie Detection System Leveraging Physiological Signals

Lie detection (polygraph) is an essential tool in forensic investigations, but traditional methods have limitations that lead to ongoing debates about their reliability and accuracy. One of the causes is that the interpretation of polygraph results relies heavily on the examiner's judgment and subjective analysis. This study aims to investigate the development of a microcontroller-based lie detection system that leverages physiological signals to detect deception, eliminating the need for polygraph examiners. We conducted a mock crime scenario involving 20 participants, including perpetrators and witnesses. The Reid method was used to question participants and elicit physiological responses, such as heart rate and skin conductance. The collected data were utilized to develop a classification baseline distinguishing between truthful and deceptive answers. The findings demonstrate that our microcontroller-based lie detector achieved a detection accuracy rate of 80%. Moreover, the utilization of this device reduced costs by up to 98% compared to traditional polygraph methods. These results suggest that implementing microcontroller technology can significantly improve the accuracy and affordability of lie-detection tools, effectively eliminating the need for polygraph examiners.