Detection of Baseline Emotion in Brow Lift Patients Using Artificial Intelligence

The widespread popularity of browlifts and blepharoplasties speaks directly to the importance that patients place on the periorbital region of the face. In literature, most esthetic outcomes are based on instinctive analysis of the esthetic surgeon, rather than on patient assessments, public opinions, or other objective means. We employed an artificial intelligence system to objectively measure the impact of brow lifts and associated rejuvenation procedures on the appearance of emotion while the patient is in repose.

We retrospectively identified all patients who underwent bilateral brow lift for visual field obstruction between 2006 and 2019. Images were analyzed using a commercially available facial expression recognition software package (FaceReader™, Noldus Information Technology BV, Wageningen, Netherlands). The data generated reflected the proportion of each emotion expressed for any given facial movement and the action units associated.

A total of 52 cases were identified after exclusion. Pre-operatively, the angry, happy, sad, scared, and surprised emotion were detected on average of 13.06%, 1.68%, 13.06%, 3.53%, and 0.97% among all the patients, respectively. Post-operatively, the angry emotion average decreased to 5.42% (p=0.009). The happy emotion increased to 9.35% (p=0.0013), while the sad emotion decreased to 5.42%. The scared emotion remained relatively the same at 3.4%, and the surprised emotion increased to 2.01%; however, these were not statistically significant.

This study proposes a paradigm shift in the clinical evaluation of brow lift and other facial esthetic surgery, implementing an existing facial emotion recognition system to quantify changes in expression associated with facial surgery.

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