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SMASH: A distributed sensing and processing garment for the classification of upper body postures

Publication Type Conference Paper
Authors Holger Harms, Oliver Amft, Daniel Roggen, Gerhard Tröster
Title SMASH: A distributed sensing and processing garment for the classification of upper body postures
Abstract This paper introduces a smart textile for posture classification. A distributed sensing and processing architecture is implemented into a loose fitting long sleeve shirt. Standardized interfaces to remote periphery support the variable placement of different sensor modalities at any location of the textile. The shirt is equipped with acceleration sensors in order to determine the postural resolution and the systems feasibility for applications in movement rehabilitation. For the garment characterization an arm posture measurement method is proposed and applied in a study with 5 users. The classification performance is analyzed on data from overall 8 users, conducting 12 posture types, relevant for shoulder and elbow joint rehabilitation. We present results for different user-modes, with classification rates of 89% for a user-independent evaluation. Moreover, the relation of body dimensions on the posture classification performance are analyzed.
Date March 2008
Proceedings Title Bodynets 2008: Proceedings of the Third International Conference on Body Area Networks
Publisher ICST
URL Publisher's website
Extra Recipient of the Best Paper Award, sponsored by the Consortium for Embedded Systems.
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Friedrich-Alexander-Universität Erlangen-Nürnberg