基于计算机视觉的患者面部偏转角度对面瘫评定的影响分析

Influence Analysis of Facial Deflection Angle on Facial Paralysis Evaluation Based on Computer Vision

目的:分析面瘫患者面部与相机光轴之间偏转角度对面瘫几何特征评估的影响。方法:基于计算机视觉单元,利用OpenCV 3.1.0+dlib 19.19方法构建人脸特征点识别系统,建立面瘫评定几何度量模型,分析计算机视觉检测范围内患者面部额状面与相机单元的夹角对面瘫量化评定参数的影响。结果:本研究开发的面部特征识别系统在面部与相机光轴偏转角度为〔-30°,30°〕之间,面部特征点距离实测值与计算机捕获的面部特征点距离平均值偏差均在1 mm之内,眼缝水平和垂直测量距离的标准差分别为(1.13,1.94)和(0.85,1.24)之间,嘴角相对于鼻尖的垂直测量距离的标准差处于(1.69,2.78)之间,具有良好的识别精度。结论:面瘫患者左右面部几何特征存在差异,获取患者面部几何特征进行康复评定是开展治疗的前提,利用计算机视觉能够获取患者面部图像,识别患者面部的几何特征和差异,并且为患者头部偏转30°以内的面瘫情况评定提供了一种可行的方案。

Objective To analyze the influence of the deflection angle between the frontal facial plane and the camera optical axis on evaluation of facial paralysis.Methods A facial feature detection system using opencv+dlib based on computer vision was developed,then,a measurement model based on facial features for facial paralysis evaluation was constructed,and the influence of the deflection angle between the frontal facial plane and the camera optical axis was analyzed.Results The experimental results demonstrate that the developed can achieve an average deviation within 1 mm between the real distance and the detection distance by computer vision when the angle between the frontal facial plane and the camera optical axis belongs to〔–30°,30°〕,while the standard deviation of the gap of eye open in the horizontal and vertical direction belong to(1.13,1.94)and(0.85,1.24),respectively.Meanwhile,the standard deviation of the distance between the mouth corners and the nose tip belongs to(1.69,2.78).The results present the developed system can obtain good detection accuracy within a set deflection angle.Conclusion Geometric deviation will be generated on facial paralysis patients,and the developed facial detection system can recognize facial geometric features and achieve good detection accuracy.It provides a solution to perform evaluation of facial paralysis even the head of the subject rotate an angle within 30°.