Contextra: Detecting Object Grasps With Low-Power Cameras and Sensor Fusion On the Wrist MHCI006

Knowing when a user picks up an object plays a vital role in many context-aware applications. For example, tracking water consumption, counting calories consumed, or reminding you to bring your keys are all context-centered scenarios involving picking up objects. In this project, we propose Contextra, a wrist-worn system that uses sensor fusion to recognize when a user grasps objects. Sensor fusion allows all parts of the grasp to be sensed in ways single channels cannot alone. In our wristband, we fuse EMG and IMU data with video captured from three low-power IR cameras. These cameras maintain privacy by using an active-illumination technique to only capture features close to the sensors. Beyond grasps alone, we see Contextra as playing a foundational role in providing continuous awareness of context triggers to extend the functionality of existing AI devices that cannot run continuously due to power and privacy concerns.