Using 2D and 3D Face Representations to Generate Comprehensive Facial Electromyography Intensity Maps

Electromyography (EMG) is a method to measure muscle activity. Physicians also use EMG to study the function of facial muscles through intensity maps (IMs) to support diagnostics and research. However, many existing visualizations neglect anatomical structures and disregard the physical properties of EMG signals. The variance of facial structures between people complicates the generalization of IMs, which is crucial for their correct interpretation. In our work, we overcome these issues by introducing a pipeline to generate anatomically correct IMs for facial muscles. An IM generation algorithm based on a template model incorporates custom surface EMG schemes and combines them with a projection method to highlight the IMs on the patient's face in 2D and 3D. We evaluate the generated and projected IMs based on their correct projection quality for six base emotions on several subjects. These visualizations deepen the understanding of muscle activity areas and indicate that a holistic view of the face could be necessary to understand facial muscle activity. Medical experts can use our approach to study the function of facial muscles and to support diagnostics and therapy.