EmoGlass: an End-to-End AI-Enabled Wearable Platform for Enhancing Self-Awareness of Emotional Health

Often, emotional disorders are overlooked due to their lack of awareness, resulting in potential mental issues. Recent advances in sensing and inference technology provide a viable path to wearable facial-expression-based emotion recognition. However, most prior work has explored only laboratory settings and few platforms are geared towards end-users in everyday lives or provide personalized emotional suggestions to promote self-regulation. We present Emo-Glass, an end-to-end wearable platform that consists of emotion detection glasses and an accompanying mobile application. Our single-camera-mounted glasses can detect seven facial expressions based on partial face images. We conducted a three-day out-oflab study (N=15) to evaluate the performance of EmoGlass. We iterated on the design of the EmoGlass application for efective self-monitoring and awareness of users' daily emotional states. We report quantitative and qualitative fndings, based on which we discuss design recommendations for future work on sensing and enhancing awareness of emotional health.

• Human-centered computing → Ubiquitous and mobile computing; Ubiquitous and mobile computing systems and tools.