ActSonic: Recognizing Everyday Activities from Inaudible Acoustic Wave Around the Body
Saif Mahmud, Vineet Parikh, Qikang Liang, Ke Li, Ruidong Zhang, Ashwin, Ajit, Vipin Gunda, Devansh Agarwal, Fran\c{c}ois Guimbreti\`ere, Cheng Zhang

TL;DR
ActSonic is a low-power, eyeglasses-integrated acoustic sensing system that recognizes 27 daily activities using inaudible ultrasonic waves and deep learning, achieving high accuracy without user-specific training.
Contribution
It introduces a novel ultrasonic sensing system embedded in eyeglasses for activity recognition, utilizing self-supervised deep learning and requiring no user-specific training data.
Findings
Achieved an average F1-score of 86.6% in real-world scenarios.
Successfully recognized 27 different activities.
Operates with low power and minimal hardware.
Abstract
We present ActSonic, an intelligent, low-power active acoustic sensing system integrated into eyeglasses that can recognize 27 different everyday activities (e.g., eating, drinking, toothbrushing) from inaudible acoustic waves around the body. It requires only a pair of miniature speakers and microphones mounted on each hinge of the eyeglasses to emit ultrasonic waves, creating an acoustic aura around the body. The acoustic signals are reflected based on the position and motion of various body parts, captured by the microphones, and analyzed by a customized self-supervised deep learning framework to infer the performed activities on a remote device such as a mobile phone or cloud server. ActSonic was evaluated in user studies with 19 participants across 19 households to track its efficacy in everyday activity recognition. Without requiring any training data from new users…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsContext-Aware Activity Recognition Systems
