Eyelid and Blink Tracking in an Animal Model of Facial Palsy.
Eyelid and Blink Tracking in an Animal Model of Facial Palsy.
复制标题
面瘫动物模型中的眼睑和眨眼追踪。
DOI：
10.1109/embc.2018.8513494
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Kearney,RobertE
中科院分区：
文献类型：
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作者：
Tsror,Guy;Guarin,DiegoL;Jowett,Nate;Kearney,RobertE
面瘫（FP）是一种因面神经损伤而导致的临床病症。我们假设，通过使用健康侧肌肉的活动作为控制输入，对肌肉进行电刺激，可以恢复受伤侧的活动。为了探索这一假设，我们使用 FP 大鼠模型，该模型将眨眼和扫动视为面部运动的感兴趣特征。本文描述了一种新方法的开发，用于自动检测和测量大鼠视频记录中的眼睑位移和眨眼。具体来说，主动轮廓方法用于在头部固定视频中定位和跟踪啮齿动物的眼睛。算法初始化，在视频第一帧中手动标记眼睛轮廓；根据能量函数自动分析后续帧，该能量函数取决于感兴趣区域中的图像特征。我们的结果表明，我们的新技术能够以 100% 的成功率检测视频录制中的眨眼，并且算法输出与手动验证之间具有高度相关性。
Facial palsy (FP) is a clinical condition resulting from damage to the facial nerve. We hypothesize that activity can be restored in the injured side, by electrical stimulation of its muscle, using the activity of muscles on the healthy side as a control input. To explore this hypothesis, we are using a rat model of FP, which treats blinking and whisking as the features of interest in facial movement. This paper describes the development of a novel methodology for the automatic detection and measurement of eyelid displacement and blinks in video records of the rat. Specifically, the active contour approach was used to localize and track rodent eyes in a head-fixed video. The algorithm is initialized manually marking the eye contour in the first frame of the video; subsequent frames are analyzed automatically based on an energy function that depends on image features in the region of interest. Our results demonstrate that our novel technique detects blinks in video recordings with a success rate of 100% and a high correlation between the algorithm output and the manual validation.