![]() Moreover, we propose a vector-based sequential forward selection (VSFS) algorithm to identify the muscle (or muscle combination) most closely associated with lying. Addressing this issue, this paper proposes an experimental paradigm with high ecological validity that uses electromyography (EMG) signals to precisely examine the role of facial muscle movements in deception detection. However, the aim of this study is to demonstrate the direct relationship between facial muscle movements and deception detection. In the existed research investigating the relationship between facial muscles and deception detection, researchers have focused almost exclusively on two muscles, i.e., zygomaticus and corrugator supercilii, based on the theoretical basis that they are highly associated with positive and negative expressions. Micro-expression, which is generated by facial muscle movements, could be a crucial cue for deception detection.
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