Automated Facial Expression Analysis: A New Framework for Comparing Facial Muscle Activity Across Individuals

Objective and precise measurement of facial muscle activity is crucial for understanding emotional expressions across diverse stimuli. However, traditional methods often require controlled lab environments, limiting real-world applicability. In this study, we introduce an automated framework that integrates wireless facial surface electromyography (sEMG) with a robust facial muscle Atlas for comprehensive facial expression analysis. This approach enables cross-subject and inter-subject measurements, facilitating applications in psychology, affective computing, and clinical research. We validate our framework by analyzing facial muscle activity in response to olfactory, visual, and auditory emotional stimuli, demonstrating its efficacy in capturing nuanced expression dynamics.Clinical relevance- This work advances emotion research by providing a scalable and objective tool for facial expression analysis, with potential applications in psychology and medical diagnostics, particularly in conditions where facial expressions play a crucial role.