Outcome Tracking in Facial Palsy

Joseph R Dusseldorp; Martinus M van Veen; Suresh Mohan; Tessa A Hadlock

doi:10.1016/j.otc.2018.07.003

Outcome Tracking in Facial Palsy

Otolaryngol Clin North Am. 2018 Dec;51(6):1033-1050. doi: 10.1016/j.otc.2018.07.003. Epub 2018 Aug 29.

Authors

Joseph R Dusseldorp¹, Martinus M van Veen², Suresh Mohan³, Tessa A Hadlock³

Affiliations

¹ Department of Otolaryngology/Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA; Department of Plastic and Reconstructive Surgery, Royal Australasian College of Surgeons, University of Sydney, City Road, Camperdown, Sydney, NSW, Australia 2006. Electronic address: joeduss@gmail.com.
² Department of Otolaryngology/Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA; Department of Plastic Surgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands.
³ Department of Otolaryngology/Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA.

PMID: 30172554
DOI: 10.1016/j.otc.2018.07.003

Abstract

Outcome tracking in facial palsy is multimodal, consisting of patient-reported outcome measures, clinician-graded scoring systems, objective assessment tools, and novel tools for layperson and spontaneity assessment. Patient-reported outcome measures are critical to understanding burden of disease in facial palsy and effects of interventions from the patient perspective. Clinician-graded scoring systems are inherently subjective and no 1 single system satisfies all needs. Objective assessment tools quantify facial movements but can be laborious. Recent advances in facial recognition technology have enabled automated facial measurements. Novel assessment tools analyze attributes such as spontaneous smile, emotional expressivity, disfigurement, and attractiveness as determined by laypersons.

Keywords: Emotionality quotient; Emotrics; Facial palsy; Layperson; Machine learning; Spontaneous smile; eFACE.

Publication types

Review

MeSH terms

Face
Facial Paralysis / therapy*
Humans
Outcome Assessment, Health Care / methods*
Severity of Illness Index
Smiling