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DOI: 10.1055/s-0041-1727694
App-based quantification of facial palsy with the Digital Facial Index
Introduction There are several clinical and software-based systems for quantifying facial nerve palsy, which are very useful for assessing the course of the disease. However, due to the time required to collect and document the data they are rarely used. Therefore, an app-based solution was implemented which uses the depth mapping camera of modern smartphones to quickly and precisely determine the extent of a unilateral facial palsy.
Material & methods An app prototype for iOS was developed which analyzes the data from the depth mapping camera of iPhones. During the measurement process, the user is asked to perform three facial movements. The so-called Digital Facial Index is calculated using a special algorithm. This classifies a facial paralysis with a value from 0 % to 100 % . In a first test group of 10 patients with unilateral facial palsy, the Digital Facial Index was determined and correlated with the Stennert index and the House-Brackmann scale.
Results After a short briefing of the patients, the measurement process was completed within 5 seconds, respectively. The calculated Digital Facial Index showed in all cases a high correlation both for the Stennert index and for the House-Brackman scale. No significant intertest variability could be detected for the results.
Discussion The promising first experiences with the app-based quantification of facial nerve palsy suggest that this method could be very helpful in everyday clinical practice. A prospective clinical study with a larger group of patients is planned to better assess the validity and reliability of the Digital Facial Index.
Poster-PDF A-1202.pdf
Conflict of interest
Der Erstautor gibt keinen Interessenskonflikt an.
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Artikel online veröffentlicht:
13. Mai 2021
© 2021. 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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