For patients with facial paralysis, the wait for return of facial function and the resulting vision risk from poor eye closure, difficulty speaking and eating from flaccid oral sphincter muscles, as well as the psychological morbidity from the inability to smile or express emotions through facial movement can be devastating. There are limited methods to assess ongoing facial nerve regeneration: clinicians rely on subjective descriptions, imprecise scales, and static photographs to evaluate facial functional recovery and thus facial nerve regeneration remains poorly understood. We propose a more precise evaluation of dynamic facial function through video-based machine learning analysis which would facilitate a better understanding of the sometimes subtle onset of facial nerve recovery and improve guidance for facial reanimation surgery. Specifically, we here present machine learning methods employing likelihood ratio tests, optimal transport theory, and Mahalanobis distances to: 1) assess the use of defined facial landmarks for binary classification of different types of facial palsy; 2) identify regions of asymmetry and potential paralysis during specific facial cues; and 3) determining severity of abnormal facial function when compared to a reference class of normal facial function. Our work presents promising results of utilizing videos, rather than static photographs, to provide robust quantitative analyses of dynamic properties for various facial movements without requiring manual assessment. The long-term potential of this project is to enable clinicians to have more accurate and timely information to make decisions for facial reanimation surgery which will have drastic consequences on quality of life for affected patients.

The authors have declared no competing interest.

This study was funded by Stanford Graduate Fellowship in Science & Engineering.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

IRB of University of California, San Diego gave ethical approval for the photo and video-based assessment at the facial nerve center (Project#210007, UCSD Facial Palsy Database).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

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Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

All data produced in the present study are available upon reasonable request to the authors.