Most everyday electrical and electromechanical objects emit small amounts of electromagnetic (EM) noise during regular operation. When a user makes physical contact with such an object, this EM signal propagates through the user, owing to the conductivity of the human body. By modifying a small, low-cost, software-defined radio, we can detect and classify these signals in real-time, enabling robust on-touch object detection. Unlike prior work, our approach requires no instrumentation of objects or the environment; our sensor is self-contained and can be worn unobtrusively on the body. We call our technique  EM-Sense  and built a proof-of-concept smartwatch implementation. Our studies show that discrimination between dozens of objects is feasible, independent of wearer, time and local environment.
['Gierad Laput', 'Chouchang Yang', 'Robert Xiao', 'Alanson P. Sample', 'Chris Harrison']
EM-Sense: Touch Recognition of Uninstrumented, Electrical and Electromechanical Objects