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Recognizing whether sensors are on the same body
Authors:Cory T Cornelius  David F Kotz
Affiliation:Department of Computer Science, Dartmouth College, Hanover, NH, 03755, USA;Institute for Security, Technology, and Society, Dartmouth College, Hanover, NH, 03755, USA
Abstract:In an open mobile health (mHealth) sensing system, users will be able to seamlessly pair sensors with their cellphone and expect the system to just work. This ubiquity of sensors, however, creates the potential for users to accidentally wear sensors that are not paired with their own cellphone. Our method probabilistically detects this situation by finding correlations between embedded accelerometers in the cellphone and sensor. We evaluate our method over a dataset of seven individuals with sensors in various positions on their body and experimentally show that our method is capable of achieving an accuracy of 85%.
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