Seokmin Choi, Yang Gao, Yincheng Jin, Se jun Kim, Jiyang Li, Wenyao Xu, Zhanpeng Jin
2022 Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies  
Recognition of facial expressions has been widely explored to represent people's emotional states. Existing facial expression recognition systems primarily rely on external cameras which make it less accessible and efficient in many real-life scenarios to monitor an individual's facial expression in a convenient and unobtrusive manner. To this end, we propose PPGface, a ubiquitous, easy-to-use, user-friendly facial expression recognition platform that leverages earable devices with built-in PPG
more » ... sensor. PPGface understands the facial expressions through the dynamic PPG patterns resulting from facial muscle movements. With the aid of the accelerometer sensor, PPGface can detect and recognize the user's seven universal facial expressions and relevant body posture unobtrusively. We conducted an user study (N=20) using multimodal ResNet to evaluate the performance of PPGface, and showed that PPGface can detect different facial expressions with 93.5 accuracy and 0.93 fl-score. In addition, to explore the robustness and usability of our proposed platform, we conducted several comprehensive experiments under real-world settings. Overall results of this work validate a great potential to be employed in future commodity earable devices.
doi:10.1145/3534597 fatcat:yr5gsyozfzfzjnyqhlwaw2kmtm