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The Capacitive Chair

  • Andreas BraunEmail author
  • Sebastian Frank
  • Reiner Wichert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9189)

Abstract

Modern office work often consists of spending long hours in a sitting position. This can cause a number of health-related issues, including chronic back pain. Ergonomic sitting requires suitably adjusted chairs and switching through a variety of different sitting positions throughout the day. Smart furniture can support this positive behavior, by recognizing poses and activities and giving suitable feedback to the occupant. In this work we present the Capacitive Chair. A number of capacitive proximity sensors are integrated into a regular office chair and can sense various physiological parameters, ranging from pose to activity levels or breathing rate recognition. We discuss a suitable sensor layouts and processing methods that enable detecting activity levels, posture and breathing rate. The system is evaluated in two user studies that test the activity recognition throughout a work week and the recognition rate of different poses.

Keywords

Capacitive proximity sensor Posture recognition Smart furniture 

Notes

Acknowledgments

We would like to thank all volunteers that participated in our studies and provided valuable feedback for future iterations. This work was partially funded by EIT ICT Labs SSP14267 and HWB13031.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andreas Braun
    • 1
    Email author
  • Sebastian Frank
    • 2
  • Reiner Wichert
    • 1
  1. 1.Fraunhofer Institute for Computer Graphics Research IGDDarmstadtGermany
  2. 2.Hochschule Rhein-MainWiesbadenGermany

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