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Facial expressions have been considered a metric reflecting a person'sengagement with a task. While the evolution of expression detection methods isconsequential, the foundation remains mostly on image processing techniquesthat suffer from occlusion, ambient light, and privacy concerns. In this paper,we propose ExpresSense, a lightweight application for standalone smartphonesthat relies on near-ultrasound acoustic signals for detecting users' facialexpressions. ExpresSense has been tested on different users in lab-scaled andlarge-scale studies for both posed as well as natural expressions. By achievinga classification accuracy of ~75% over various basic expressions, we discussthe potential of a standalone smartphone to sense expressions through acousticsensing.

ExpresSense: Exploring a Standalone Smartphone to Sense Engagement of Users from Facial Expressions Using Acoustic Sensing