SAWSense: Using Surface Acoustic Waves for Surface bound Event Recognition

Abstract: Enabling computing systems to understand user interactions with everyday surfaces and objects can drive a wide range of applications. However, existing vibrationbased sensors accelerometers) lack the sensitivity to detect light touch gestures or the bandwidth to recognize activity containing highfrequency components. Conversely, microphones are highly susceptible to environmental noise, degrading performance. Each time an object impacts a surface, Surface Acoustic Waves (SAWs) are generated that propagate along the airtosurface boundary. This work repurposes a Voice PickUp Unit (VPU) to capture SAWs on surfaces (including smooth surfaces, odd geometries, and fabrics) over long distances and in noisy environments. Our customdesigned signal acquisition, processing, and machine learning pipeline demonstrates utility in both interactive and activity recognition applications, such as classifying trackpadstyle gestures on a desk and recognizing 16 cookingrelated activities, all with +97