  We introduce MunchSonic, an AI-powered active acoustic sensing system
integrated into eyeglasses to track fine-grained dietary actions. MunchSonic
emits inaudible ultrasonic waves from the eyeglass frame, with the reflected
signals capturing detailed positions and movements of body parts, including the
mouth, jaw, arms, and hands involved in eating. These signals are processed by
a deep learning pipeline to classify six actions: hand-to-mouth movements for
food intake, chewing, drinking, talking, face-hand touching, and other
activities (null). In an unconstrained study with 12 participants, MunchSonic
achieved a 93.5% macro F1-score in a user-independent evaluation with a
2-second resolution in tracking these actions, also demonstrating its
effectiveness in tracking eating episodes and food intake frequency within
those episodes.
