Automatic Patient Pose Estimation Using Pressure Sensing Mattresses

  • Robert GrimmEmail author
  • Johann Sukkau
  • Joachim Hornegger
  • Günther Greiner
Part of the Informatik aktuell book series (INFORMAT)


We present a system to automatically estimate the body pose of a reclined patient, based on measurement data from a pressure sensing mattress. It can be used to replace or reduce manual input in clinical imaging procedures and thus improve the workflow. The proposed method consists of two stages. First, the body posture is classified into prone, supine, and left and light lateral orientation by a k-nearestneighbor classifier. In the second algorithmic stage, a modified optimization scheme based on Powell’s direction set method fits a model of the human body to the observed pressure distribution. Thus, the position of important body landmarks is estimated. For our database of 143 measurements from 16 subjects, a mean classification rate of 96.0 % was achieved for the posture, and an average localization error of 6.95 cm for the body parts.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Schaller C, Rohkohl C, Penne J, et al. Inverse C-arm positioning for interventional procedures using real-time body part detection. Lect Notes Computer Sci. 2009; p. 549–56.Google Scholar
  2. 2.
    Moeslund TB, Hilton A, Krüger V. A survey of advances in vision-based human motion capture and analysis. Comp Vis Imag Under. 2006;104(2-3):90–126.CrossRefGoogle Scholar
  3. 3.
    Lee MW, Nevatia R. Human pose tracking in monocular sequence using multilevel structured models. IEEE Trans Pat Anal Mach Intell. 2009;31(1):27–38.CrossRefGoogle Scholar
  4. 4.
    Harada T, Mori T, Nishida Y, et al. Body parts positions and posture estimation system based on pressure distribution image. In: Proc IEEE Int Conf Robot Autom. vol. 2; 1999. p. 968–75.Google Scholar
  5. 5.
    Harada T, Sato T, Mori T. Human motion tracking system based on skeleton and surface integration model using pressure sensors distribution bed. In: Proc Workshop on Human Motion; 2000. p. 99–106.Google Scholar
  6. 6.
    Seo KH, Oh C, Lee JJ. Intelligent bed robot system: pose estimation using sensor distribution mattress. In: Proc IEEE Int Conf Robot Biomim; 2004. p. 828–32.Google Scholar
  7. 7.
    Powell MJD. An efficient method for finding the minimum of a function of several variables without calculating derivatives. Comput J. 1964;7:155–62.MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Robert Grimm
    • 1
    • 2
    Email author
  • Johann Sukkau
    • 3
  • Joachim Hornegger
    • 1
  • Günther Greiner
    • 2
  1. 1.Pattern Recognition LabUniversity of Erlangen-NurembergErlangen-NurembergGermany
  2. 2.Chair for Computer GraphicsUniversity of Erlangen-NurembergErlangen-NurembergGermany
  3. 3.Siemens AG, Healthcare MRErlangenGermany

Personalised recommendations