Automated and objective action coding of facial expressions in patients with acute facial palsy.

Authors:
Daniel Haase
Daniel Haase
Friedrich-Schiller University of Jena
Jena | Germany
Gerd Fabian Volk
Gerd Fabian Volk
Jena University Hospital
Germany
Joachim Denzler
Joachim Denzler
Friedrich Schiller University of Jena
Orlando Guntinas-Lichius
Orlando Guntinas-Lichius
Jena University Hospital
Germany

Eur Arch Otorhinolaryngol 2015 May 6;272(5):1259-67. Epub 2014 Nov 6.

Department of Computer Science, Friedrich Schiller University, Jena, Germany.

Aim of the present observational single center study was to objectively assess facial function in patients with idiopathic facial palsy with a new computer-based system that automatically recognizes action units (AUs) defined by the Facial Action Coding System (FACS). Still photographs using posed facial expressions of 28 healthy subjects and of 299 patients with acute facial palsy were automatically analyzed for bilateral AU expression profiles. All palsies were graded with the House-Brackmann (HB) grading system and with the Stennert Index (SI). Changes of the AU profiles during follow-up were analyzed for 77 patients. The initial HB grading of all patients was 3.3 ± 1.2. SI at rest was 1.86 ± 1.3 and during motion 3.79 ± 4.3. Healthy subjects showed a significant AU asymmetry score of 21 ± 11 % and there was no significant difference to patients (p = 0.128). At initial examination of patients, the number of activated AUs was significantly lower on the paralyzed side than on the healthy side (p < 0.0001). The final examination for patients took place 4 ± 6 months post baseline. The number of activated AUs and the ratio between affected and healthy side increased significantly between baseline and final examination (both p < 0.0001). The asymmetry score decreased between baseline and final examination (p < 0.0001). The number of activated AUs on the healthy side did not change significantly (p = 0.779). Radical rethinking in facial grading is worthwhile: automated FACS delivers fast and objective global and regional data on facial motor function for use in clinical routine and clinical trials.

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May 2015
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