Abstract

During COVID, much of the world wore masks covering their lower faces to prevent the spread of disease. These masks cover lower facial features, but how vital are these lower facial features to the recognition of facial expressions of emotion? Going beyond the Ekman 6 emotions, in Study 1 (N = 372), we used a multilevel logistic regression to examine how artificially rendered masks influence emotion recognition from static photos of facial muscle configurations for many commonly experienced positive and negative emotions. On average, masks reduced emotion recognition accuracy by 17% percent for negative emotions and 23% for positive emotions. In Study 2 (N = 338), we asked whether these results generalised to multimodal full-body expressions of emotions, accompanied by vocal expressions. Participants viewed videos from a previously validated set, where the lower facial features were blurred from the nose down. Here, though the decreases in emotion recognition were noticeably less pronounced, highlighting the power of multimodal information, we did see important decreases for certain specific emotions and for positive emotions overall. Results are discussed in the context of the social and emotional consequences of compromised emotion recognition, as well as the unique facial features which accompany certain emotions.