Three Parameters Impact the Perception of Smile Asymmetry in Patients with Facial Paralysis.

IF 1.6 3区 医学 Q2 SURGERY
Rachel Skladman, David Chi, Gary B Skolnick, Alison K Snyder-Warwick
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Abstract

Background: The ability to smile is impaired in patients with facial palsy, and objective parameters assessing smile symmetry to guide treatment are not well elucidated. Objective: This study seeks to identify objective facial measurements that relate smile recognition, perception of smile asymmetry, and perceived emotions from photographs of individuals with asymmetrical smiles compared with control photographs of individuals without smile asymmetry as measured by a photograph analysis application. Methods: Fifty-six photographs of smiles were categorized using objective perioral morphometric measurements (Emotrics). A photographic survey of these smiles was disseminated with queries regarding smile symmetry, smile recognition, and emotion perception. Generalized linear mixed modeling (GLMM) was performed to assess the effect of facial measurements on survey responses. Results: From 756 survey responses, smile symmetry predicted for smile recognition (F = 1084, p < 0.001) and emotion perception (F = 422, p < 0.001). Correlation analysis and GLMM identified three parameters (lower lip height, commissure position, and commissure height) that predicted smile recognition (F = 1040, p < 0.001), emotion perception (F = 976, p < 0.001), and symmetry (F = 1248, p < 0.001). Lower lip height (β = -57.84, p < 0.001) and commissure position (β = -29.41, p < 0.001) were the most significant drivers. Conclusions: Correcting lower lip height and commissure position represents efficacious clinical benchmarks for improving smile recognition by reducing smile asymmetry and conveying negative emotions.

三个参数影响面瘫患者对微笑不对称的感知
背景:面瘫患者的微笑能力会受到影响,而评估微笑对称性以指导治疗的客观参数尚未得到很好的阐明。研究目的本研究旨在通过照片分析应用软件,将微笑不对称患者的照片与无微笑不对称患者的对照照片进行比较,从而确定与微笑识别、微笑不对称感知和感知情绪相关的客观面部测量值。研究方法使用客观口周形态测量法(Emotrics)对 56 张微笑照片进行分类。对这些微笑的照片进行了调查,并询问了微笑对称性、微笑识别和情绪感知方面的问题。采用广义线性混合模型(GLMM)评估面部测量对调查回答的影响。结果显示在 756 份调查回复中,微笑对称性预测了微笑识别(F = 1084,p < 0.001)和情绪感知(F = 422,p < 0.001)。相关分析和 GLMM 确定了三个参数(下唇高度、会厌位置和会厌高度)对微笑识别(F = 1040,p < 0.001)、情绪感知(F = 976,p < 0.001)和对称性(F = 1248,p < 0.001)的预测作用。下唇高度(β = -57.84,p < 0.001)和会厌位置(β = -29.41,p < 0.001)是最显著的驱动因素。结论矫正下唇高度和会厌位置是通过减少微笑不对称和传达负面情绪来提高微笑识别率的有效临床基准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.70
自引率
30.00%
发文量
159
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