Subjective classification of patients with facial palsy using grading systems like
House-Brackmann-Scale or the Sunnybrook Grading scale still is the standard in clinical
routine. Because subjective grading has a limited intra-rater reliability and inter-rater
reliability automated classification systems are urgently needed. This would also
allow a better comparison of studies (for instance to compare different types of facial
nerve reconstructive surgery) and patients with different ethnic background. In Jena,
Germany, we have established an interdisciplinary Facial Nerve Center dealing with
different kind of facial palsies (peripheral, central palsy) and different types of
therapies (conservative, surgery). We have developed and validated a video tutorial
to standardize the recording of facial nerve movements in patients with different
types of facial palsy. The videos allow an evaluation of all important facial nerve
functions. Furthermore, we habe developed together with the chair of image analysis
a prototype of a new software based on machine learning algorithms to classify facial
palsies automatically based on standardized photographs. At the moment we transfer
the technology on video data. We would like to perform a bi-national Chinese-German
clinical trial to train the algorithm also for Chinese patients and validate the results
in this international setting.
