Exploratory Study on Emotional Facial Expressions of Individuals with Visual Disabilities in Digital Communication Platform

Abstract

This study examined how individuals with visual disabilities express emotions via facial expressions on video conferencing platforms. Twenty-eight adults posed eight basic emotions via Zoom. Facial muscle activity was analyzed using the Facial Action Coding System (FACS), which codes facial movements as Action Units (AUs). Distinct AU patterns emerged for most emotions, though sadness lacked consistency. Some emotions shared overlapping AUs. Neutral expressions sometimes showed muscle activity, while some non-neutral emotions did not. Expression patterns varied by valence, arousal, and their interaction. These findings suggest that facial expressions in individuals with visual disabilities often differ from typical emotion–muscle patterns, highlighting the need for inclusive emotion-sensing technologies that accommodate diverse expressions and a better understanding of affective communication in remote settings.