A Comprehensive Assessment Report of Facial Paralysis

What is it about?

The goal of this research is to develop a comprehensive evaluation system for Facial Paralysis based on the Kinect v2 camera. The system is able to assess the facial functions and classify the paralysis severity level based on Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The aim of this paper is to describe the development and testing of the facial paralysis assessment phase using a dataset of 375 records from 13 unilateral facial paralysis patients. The facial paralysis assessment includes three modules: 1. The symmetry assessment, 2. Facial movements recognition, 3. Facial functions assessment. The developed FP grading system provides a detailed quantitative report and has significant advantages over the existing grading scales. It is fast, easy to use, user-independent, low cost, quantitative, and automated and hence it is suitable to be used as a clinical tool.

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Photo by Alexander Grey on Unsplash

Photo by Alexander Grey on Unsplash

Why is it important?

A dataset of 375 records from 13 unilateral FP patients was compiled for this study. The work presented in this paper to the best of our knowledge is unique in assessing the facial paralysis degree and evaluating the performance of the five functions based on the 3D landmarks and facial animation units extracted by the Kinect sensor. The developed FP grading system provides a detailed quantitative report and has significant advantages over the existing grading scales. It is fast, easy to use, user-independent, low cost, quantitative, and automated and hence it is suitable to be used as a clinical tool.