Customized Precision Facial Assessment: An AI-assisted Analysis of Facial Microexpressions for Advanced Aesthetic Treatment

Abstract

We introduced a novel protocol based on an artificial intelligence (AI)-assisted analytic system for facial expressions, Customized Precision Facial Assessment (CPFA), to evaluate and quantify the microexpressions of aesthetic concern. With the help of CPFA, physicians may be able to conduct static and dynamic assessments for the microexpressions of the ir patients and perform quantitative measurements before and after the treatments. Through the detection of microexpressions and its active action units of facial muscles, physicians are more likely to optimize the treatment with minimal intervention by precise localization of the foci of aesthetic concern. We presented 3 cases who received neuromodulators and injectable fillers, and we showed the differences in the area of treatment and outcomes of procedures between the CPFA-oriented treatments and human-facilitated ones. We found negative facial expressions decreased in all 3 cases in the group of CPFA while they decreased in only case 1 and case 2 in the group of human facilitated treatment. The CPFA group has more significant decrease in negative facial expression scores than the human group. This pilot study demonstrates that CPFA can objectively recognize and quantify the facial action units associated with negative emotions, and the physician may be able to customize the treatment for individuals accordingly with promising results.

Fig. 1.

An example of facial coding system. Action units (AUs) and its corresponding facial expression muscles. DAO, depressor anguli oris. Reprinted with permission from Zarins U, Kondrats S. Anatomy of Facial Expression. © Exonicus, Inc.; 2017.