Automatic Coding of Facial Expressions of Pain: Are We There Yet?





Faculty/Professorship: Physiological Psychology  ; Cognitive Systems  
Author(s): Lautenbacher, Stefan ; Hassan, Teena; Seuß, Dominik; Loy, Frederik ; Garbas, Jens-Uwe; Schmid, Ute  ; Kunz, Miriam
Title of the Journal: Pain research & management
ISSN: 1918-1523, 1203-6765
Publisher Information: London [u.a.] : Hindawi
Year of publication: 2022
Volume: 2022
Pages: 8
Year of first publication: 2022
Language(s): English
DOI: 10.1155/2022/6635496
Abstract: 
Introduction. The experience of pain is regularly accompanied by facial expressions. The gold standard for analyzing these facial expressions is the Facial Action Coding System (FACS), which provides so-called action units (AUs) as parametrical indicators of facial muscular activity. Particular combinations of AUs have appeared to be pain-indicative. The manual coding of AUs is, however, too time- and labor-intensive in clinical practice. New developments in automatic facial expression analysis have promised to enable automatic detection of AUs, which might be used for pain detection. Objective. Our aim is to compare manual with automatic AU coding of facial expressions of pain. Methods. FaceReader7 was used for automatic AU detection. We compared the performance of FaceReader7 using videos of 40 participants (20 younger with a mean age of 25.7 years and 20 older with a mean age of 52.1 years) undergoing experimentally induced heat pain to manually coded AUs as gold standard labeling. Percentages of correctly and falsely classified AUs were calculated, and we computed as indicators of congruency, “sensitivity/recall,” “precision,” and “overall agreement (F1).” Results. The automatic coding of AUs only showed poor to moderate outcomes regarding sensitivity/recall, precision, and F1. The congruency was better for younger compared to older faces and was better for pain-indicative AUs compared to other AUs. Conclusion. At the moment, automatic analyses of genuine facial expressions of pain may qualify at best as semiautomatic systems, which require further validation by human observers before they can be used to validly assess facial expressions of pain.
GND Keywords: Schmerz; Mimik
Keywords: pain, facial expression, coding
DDC Classification: 610 Medicine & health  
RVK Classification: YI 5793   
Peer Reviewed: Ja
International Distribution: Ja
Open Access Journal: Ja
Type: Article
URI: https://fis.uni-bamberg.de/handle/uniba/54265
Release Date: 27. June 2022