Gesture spotting with body-worn inertial sensors to detect user activities

H. Junker, O.D. Amft, P. Lukowicz, G. Tröster

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We present a method for spotting sporadically occurring gestures in a continuous data stream from body-worn inertial sensors. Our method is based on a natural partitioning of continuous sensor signals and uses a two-stage approach for the spotting task. In a first stage, signal sections likely to contain specific motion events are preselected using a simple similarity search. Those preselected sections are then further classified in a second stage, exploiting the recognition capabilities of hidden Markov models. Based on two case studies, we discuss implementation details of our approach and show that it is a feasible strategy for the spotting of various types of motion events. © 2007 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)2010-2024
JournalPattern Recognition
Issue number6
Publication statusPublished - 2008


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