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

要旨

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 EmoGlass, 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-of-lab study (N=15) to evaluate the performance of EmoGlass. We iterated on the design of the EmoGlass application for effective self-monitoring and awareness of users' daily emotional states. We report quantitative and qualitative findings, based on which we discuss design recommendations for future work on sensing and enhancing awareness of emotional health.

著者
Zihan Yan
Zhejiang University, Hangzhou, China
Yufei Wu
Zhejiang University, Hangzhou, China
Yang Zhang
University of California, Los Angeles, Los Angeles, California, United States
Xiang 'Anthony' Chen
UCLA, Los Angeles, California, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3501925

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Intelligent Systems, Human-AI Collaboration

383-385
5 件の発表
2022-05-04 01:15:00
2022-05-04 02:30:00