Physiological Psychology, University of Bamberg, Bamberg, Germany.
Department of Medical Psychology and Sociology, University of Augsburg, Augsburg, Germany.
Scand J Pain. 2020 Dec 2;21(1):174-182. doi: 10.1515/sjpain-2020-0078. Print 2021 Jan 27.
The decoding of facial expressions of pain plays a crucial role in pain diagnostic and clinical decision making. For decoding studies, it is necessary to present facial expressions of pain in a flexible and controllable fashion. Computer models (avatars) of human facial expressions of pain allow for systematically manipulating specific facial features. The aim of the present study was to investigate whether avatars can show realistic facial expressions of pain and how the sex of the avatars influence the decoding of pain by human observers.
For that purpose, 40 female (mean age: 23.9 years) and 40 male (mean age: 24.6 years) observers watched 80 short videos showing computer-generated avatars, who presented the five clusters of facial expressions of pain (four active and one stoic cluster) identified by Kunz and Lautenbacher (2014). After each clip, observers were asked to provide ratings for the intensity of pain the avatars seem to experience and the certainty of judgement, i.e. if the shown expression truly represents pain.
Results show that three of the four active facial clusters were similarly accepted as valid expressions of pain by the observers whereas only one cluster ("raised eyebrows") was disregarded. The sex of the observed avatars influenced the decoding of pain as indicated by increased intensity and elevated certainty ratings for female avatars.
The assumption of different valid facial expressions of pain could be corroborated in avatars, which contradicts the idea of only one uniform pain face. The observers' rating of the avatars' pain was influenced by the avatars' sex, which resembles known observer biases for humans. The use of avatars appeared to be a suitable method in research on the decoding of the facial expression of pain, mirroring closely the known forms of human facial expressions.
面部疼痛表情的解码在疼痛诊断和临床决策中起着至关重要的作用。对于解码研究，有必要以灵活和可控的方式呈现疼痛的面部表情。人类疼痛面部表情的计算机模型（化身）允许系统地操作特定的面部特征。本研究的目的是调查化身是否可以展示真实的疼痛面部表情，以及化身的性别如何影响人类观察者对疼痛的解码。
为此，40 名女性（平均年龄：23.9 岁）和 40 名男性（平均年龄：24.6 岁）观察者观看了 80 个短视频，展示了由 Kunz 和 Lautenbacher（2014）确定的五个疼痛面部表情簇（四个主动簇和一个静止簇）的计算机生成的化身。在每个片段之后，观察者被要求对化身似乎经历的疼痛强度和判断的确定性（即所示表情是否真的代表疼痛）进行评分。
结果表明，四个主动面部簇中的三个被观察者同样认为是有效疼痛表情，而只有一个簇（“挑眉”）被忽略。观察到的化身的性别影响了疼痛的解码，表现为女性化身的强度和确定性评分增加。
可以在化身中证实不同的有效疼痛面部表情的假设，这与只有一个统一的疼痛面孔的想法相矛盾。观察者对化身疼痛的评分受到化身性别的影响，这类似于对人类观察者已知的偏见。化身的使用似乎是研究面部疼痛表情解码的一种合适方法，与已知的人类面部表情形式非常相似。
