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

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.

• Type: Journal
• Year: 2008
• Where: PR
• Authors: Holger Junker, Oliver Amft, Paul Lukowicz, Gerhard Tröster
• Keywords: Continuous Sensor Signals, Motion Events, PR 2008, Specific Motion Events