CC BY-NC-ND 4.0 · Laryngorhinootologie 2019; 98(S 02): S129
DOI: 10.1055/s-0039-1686374
Abstracts
Otology

Automatic analysis of the function of the facial nerve

Z Gao
1   Peking Union Medical College Hospital, Beijing, China
› Author Affiliations
 
 

    Facial paralysis caused by various reasons is common in clinical practice. Accurate evaluation of facial nerve function have a great influence on the efficacy of treatment. Traditional subjective grading systems bear inter-rater differences, and is not sensitive to recovery. Therefore, we developed a three-dimensional dynamic quantitative analysis system (3-D ASFM) based on facial motion, so as to quickly perform a complete facial paralysis evaluation and collect a set of facial motion parameters.

    Facial three-dimensional dynamic quantitative analysis system (3D-ASFM) (Figure.1) consists of three parts: data collection, data processing and output, and fixation system. The data collection part is composed of six near-infrared array camera (frequency of 60 frames/s) placed in symmetrical "L” shape. Controlled by multi-way synchronization controller, each camera capture motions simultaneously. The customized facial motion capture software is the core of the data processing part. The fixation part consists of a fixing head frame and an integrated fixed chair. The fixation system is mounted on mastoids and the occipital protrusion, which maintain the system relatively static to the skull and not affect the facial movements of the subject. Three markers are placed in the front tip of the system. Once the process of measuring is started, CCD cameras capture the reflected light of subjects from face under the control of multi-channel synchronous controller; customized software calculate online and reconstruction and analyze offline.


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    Professor, MD, PhD Zhiqiang Gao
    Peking Union Medical College Hospital,
    No.1, Shuaifuyuan, Wangfujing, Dongcheng District, 100730
    Beijing, China

    Publication History

    Publication Date:
    23 April 2019 (online)

    © 2019. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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