Continuous Identification in Smart Environments Using Wrist-Worn Inertial Sensors

Abstract

In this paper, we propose a new approach capable of performing continuous identification of users in home and office environments based on hand and arm motion patterns obtained from a wrist-worn inertial measurement unit (IMU). Different from state-of-the-art methods, our approach is not constrained to particular types of movements, gestures, or activities, thus allowing users to perform freely and unconstrained their daily routines while the identification takes place. We evaluate our approach by conducting an in the lab study and two in-situ studies, one in home environment and one in office environment. Our studies involved a total of 29 different participants and the data collected corresponds to approximately 256 hours. The results obtained in the studies indicate that our approach is able to perform continuous user identification with an accuracy of 0.88 for office environments and 0.71 for the average size of a household.