Recognizing Upper Body Postures using Textile Strain Sensors

Publication Type Conference Paper
Authors Corinne Mattmann, Oliver Amft, Holger Harms, Gerhard Tröster, Frank Clemens
Title Recognizing Upper Body Postures using Textile Strain Sensors
Abstract In this paper we present a garment prototype using strain sensors to recognize upper body postures. A novel thermoplastic elastomer strain sensor was used for measuring strain in the clothing. This sensor has a linear resistance response to strain, a small hysteresis and can be fully integrated into textile. A study was conducted with eight participants wearing the garment and performing a total of 27 upper body postures. A Naive Bayes classification was applied to identify the different postures. Nearly a complete recognition rate of 97% was achieved when the classification was adapted to the individual participant. A classification rate of 84% was achieved for an all-user classification and 65% for an independent user. These results show the feasibility to recognize postures with our setup, even in an unseen user setting. Furthermore, we used the garment prototype in a gym experiment to explore its potential for rehabilitation and fitness training. Intensity, speed and number of repetitions could be obtained from the garment sensor data.
Date October 2007
Proceedings Title ISWC 2007: Proceedings of the 11th IEEE International Symposium on Wearable Computers
Publisher IEEE
Pages 29–36
DOI 10.1109/ISWC.2007.4373773
Extra Recipient of the IEEE ISWC 2007 Best Paper Award.
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Friedrich-Alexander-Universität Erlangen-Nürnberg