Lie Detection System using Multimodal Biometric Analysis

Abstract

Polygraphs and other conventional lie detection techniques have come under fire for their inaccurate results, which are attributed to individual physiological variations and anxiety. To deal with these restrictions, the innovative method known as multimodal biometric analysis was proposed. This cutting-edge technique combines physiological and behavioral indicators, such as skin conductance, facial expressions, and eye movements, to identify dishonesty. The system analyses many data streams at once in an effort to spot tiny patterns linked to lying, such altered facial expressions or an increased blink rate. Human communication relies heavily on emotions, and nonverbal clues like facial expressions have a big influence on how people connect with one another. These discoveries have been integrated into computer vision and other emotion identification technologies. Combining sentiment analysis with emotion detection Physical characteristics are also utilized to identify lies. Heart rate and skin resistance changes are used as another type of signals in proposed method. This paper explores the potential of such technologies to enhance investigative practices. It is verified by visual and graphical methods using different conditions. The proposed method also uses changes in skin resistance and heart rate as signals. The potential of these technologies to improve investigative techniques is examined in this research. It is confirmed using graphical and visual techniques under various circumstances.