EM-Sense: Touch Recognition of Uninstrumented Electrical and Electromechanical Objects

Gierad Laput, Chouchang Yang, Robert Xiao, Alanson Sample, Chris Harrison (UIST 2015)

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.

 

 

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Laput G., Yang, C., Xiao, R., Sample, A., Harrison, C. EM-Sense: Touch Recognition of Uninstrumented Electrical and Electromechanical Objects
In Proceedings of the 28th annual ACM Symposium on User Interfaces Software and Technology (UIST '15).

 

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