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European Archives of Oto-Rhino-Laryngology

, Volume 272, Issue 5, pp 1259–1267 | Cite as

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

  • Daniel Haase
  • Laura Minnigerode
  • Gerd Fabian Volk
  • Joachim Denzler
  • Orlando Guntinas-LichiusEmail author
Miscellaneous

Abstract

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.

Keywords

Facial nerve Mimic muscles Asymmetry Facial Action Coding System Grading Palsy 

Notes

Acknowledgments

We thank Astrid Wetzel (Media Center, Jena University Hospital) for the photographs of all healthy subjects and patients. We thank Wolfgang H. Miltner (Department of Biological and Clinical Psychology, Friedrich Schiller University Jena) for critical reading of the manuscript.

Conflict of interest

The authors indicate that they have no conflict of interest.

Supplementary material

405_2014_3385_MOESM1_ESM.jpg (1.8 mb)
Supplement Fig. 1. Standard set of photographs of facial expression for each healthy subject and patient. (JPEG 1883 kb)
405_2014_3385_MOESM2_ESM.jpg (430 kb)
Supplement Fig. 2. Example of automated feature point localization on the healthy side (A) and on the paralyzed side (B; mirrored to the right side!) in the standardized photography with the patient showing his teeth
405_2014_3385_MOESM3_ESM.docx (69 kb)
Supplementary material 3 (DOCX 69 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Daniel Haase
    • 1
  • Laura Minnigerode
    • 2
    • 3
  • Gerd Fabian Volk
    • 2
    • 3
  • Joachim Denzler
    • 1
  • Orlando Guntinas-Lichius
    • 2
    • 3
    Email author
  1. 1.Department of Computer ScienceFriedrich Schiller UniversityJenaGermany
  2. 2.Department of OtorhinolaryngologyUniversity Hospital JenaJenaGermany
  3. 3.Facial Nerve CenterUniversity Hospital JenaJenaGermany

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