International Journal of Computer Vision

, Volume 122, Issue 2, pp 212–227

Automatic Sleep System Recommendation by Multi-modal RBG-Depth-Pressure Anthropometric Analysis

  • Cristina Palmero
  • Jordi Esquirol
  • Vanessa Bayo
  • Miquel Àngel Cos
  • Pouya Ahmadmonfared
  • Joan Salabert
  • David Sánchez
  • Sergio Escalera
Article

DOI: 10.1007/s11263-016-0919-0

Cite this article as:
Palmero, C., Esquirol, J., Bayo, V. et al. Int J Comput Vis (2017) 122: 212. doi:10.1007/s11263-016-0919-0

Abstract

This paper presents a novel system for automatic sleep system recommendation using RGB, depth and pressure information. It consists of a validated clinical knowledge-based model that, along with a set of prescription variables extracted automatically, obtains a personalized bed design recommendation. The automatic process starts by performing multi-part human body RGB-D segmentation combining GrabCut, 3D Shape Context descriptor and Thin Plate Splines, to then extract a set of anthropometric landmark points by applying orthogonal plates to the segmented human body. The extracted variables are introduced to the computerized clinical model to calculate body circumferences, weight, morphotype and Body Mass Index categorization. Furthermore, pressure image analysis is performed to extract pressure values and at-risk points, which are also introduced to the model to eventually obtain the final prescription of mattress, topper, and pillow. We validate the complete system in a set of 200 subjects, showing accurate category classification and high correlation results with respect to manual measures.

Keywords

Sleep system recommendation RGB-Depth data Pressure imaging Anthropometric landmark extraction Multi-part human body segmentation 

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Cristina Palmero
    • 1
  • Jordi Esquirol
    • 2
  • Vanessa Bayo
    • 2
  • Miquel Àngel Cos
    • 2
  • Pouya Ahmadmonfared
    • 1
  • Joan Salabert
    • 3
  • David Sánchez
    • 3
  • Sergio Escalera
    • 1
    • 4
  1. 1.Computer Vision CenterCerdanyola del VallèsSpain
  2. 2.Servei Universitari de Recerca en Fisioteràpia (S.U.R.F), Escola Universitària GimbernatSant Cugat del VallèsSpain
  3. 3.Dormity.com®Sant Cugat del VallèsSpain
  4. 4.Dept. Matemàtica Aplicada i Anàlisi, UBBarcelonaSpain

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