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EM-Sense: Touch Recognition of Uninstrumented, Electrical and Electromechanical Objects
Gierad Laput, Chouchang Yang, Robert Xiao, Alanson P Sample, Chris Harrison

Abstract:
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.

ACM DL: http://dl.acm.org/citation.cfm?id=280...
DOI: http://dx.doi.org/10.1145/2807442.280...