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动态,自动化面部分析的使用在量化口腔眼部同运动

Angela Renne¹, Jeffrey Heaton², Adeeb Derakhshan³

¹Division of Facial Plastic and Reconstructive Surgery, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Facial plastic surgery & aesthetic medicine

|December 29, 2025

概括

动态面部跟踪量化了异常性面部麻 (IFP) 中的口眼协. 的动作揭示了明显的眼裂不对称性,有助于治疗计划.

科学领域:

眼科医生眼科眼科
神经学神经学
生物医学工程生物医学工程

背景情况:

口眼协同运动经常跟随异常性面部 (IFP).
对IFP眼裂变的客观,动态量化是有限的.
现有的方法缺乏动态评估与眼动相关的眼动异常.

研究的目的:

客观地测量IFP患者的眼裂变,使用自动面部跟踪.
量化动态的,表达特异的口眼协调缺陷.
建立一种新的,客观的方法来评估协同运动的严重程度.

主要方法:

一个病例控制研究涉及12个对照组和30名IFP患者.
基于视频的新型面部追踪软件评估了眼裂尺寸.
测量是在休息时和微笑,笑声和的表情时进行的.

主要成果:

帕克林表现出最显著的不对称性 (p < 0.001),麻侧面的眼裂减少更大.
在微笑或笑声表达时没有发现显著的不对称性.
动态建模表明,缩导致了眼裂对称度的最快,最大的下降 (斜率 = -0.196,p < 0.001).

结论:

动态面部跟踪准确量化IFP的表达特异性口眼协调障碍.
是与协同运动相关的眼裂不对称性的关键指标.
这些客观数据可以为IFP的治疗策略和患者咨询提供信息.

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