Cory Cornelius, Zachary Marois, Jacob Sorber, Ron Peterson, Shrirang Mare, and David Kotz. Vocal resonance as a biometric for pervasive wearable devices. Technical Report TR2014-747, Dartmouth Computer Science, February 2014.

Abstract: We anticipate the advent of body-area networks of pervasive wearable devices, whether for health monitoring, personal assistance, entertainment, or home automation. In our vision, the user can simply wear the desired set of devices, and they "just work"; no configuration is needed, and yet they discover each other, recognize that they are on the same body, configure a secure communications channel, and identify the user to which they are attached. This paper addresses a method to achieve the latter, that is, for a wearable device to identify the wearer, allowing sensor data to be properly labeled or personalized behavior to be properly achieved. We use vocal resonance, that is, the sound of the person's voice as it travels through the person's body. By collecting voice samples from a small wearable microphone, our method allows the device to determine whether (a) the speaker is indeed the expected person, and (b) the microphone device is physically on the speaker's body. We collected data from 25 subjects, demonstrate the feasibility of a prototype, and show that our method works with 77% accuracy when a threshold is chosen a priori.

Keywords: mheath, security, privacy

BibTeX

PDF (3994K)

Copyright © 2014 by the authors.