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Where am i: recognizing on-body positions of wearable sensors

Kai Kunze; Paul Lukowicz; Holger Junker; Gerhard Tröster
In: Proceedings of the First international conference on Location- and Context-Awareness. International Workshop on Location- and Context-Awareness (LoCa-2005), 1st, May 12-13, Oberpfaffenhofen, Germany, Pages 264-275, Lecture Notes in Computer Science (LNCS), Vol. 3479, ISBN 3-540-25896-5, 978-3-540-25896-4, Springer-Verlag, 2005.


The paper describes a method that allows us to derive the location of an acceleration sensor placed on the user's body solely based on the sensor's signal. The approach described here constitutes a first step in our work towards the use of sensors integrated in standard appliances and accessories carried by the user for complex context recognition. It is also motivated by the fact that device location is an important context (e.g. glasses being worn vs. glasses in a jacket pocket). Our method uses a (sensor) location and orientation invariant algorithm to identify time periods where the user is walking and then leverages the specific characteristics of walking motion to determine the location of the body-worn sensor. In the paper we outline the relevance of sensor location recognition for appliance based context awareness and then describe the details of the method. Finally, we present the results of an experimental study with six subjects and 90 walking sections spread over several hours indicating that reliable recognition is feasible. The results are in the low nineties for frame by frame recognition and reach 100% for the more relevant event based case.

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