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Video-based discomfort detection for infants

  • Yue Sun
  • Caifeng ShanEmail author
  • Tao Tan
  • Xi Long
  • Arash Pourtaherian
  • Svitlana Zinger
  • Peter H. N. de With
Special Issue Paper
  • 137 Downloads

Abstract

Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use.

Keywords

Infant discomfort Face detection Discomfort/stress detection Facial expression recognition 

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yue Sun
    • 1
  • Caifeng Shan
    • 2
    Email author
  • Tao Tan
    • 1
  • Xi Long
    • 1
  • Arash Pourtaherian
    • 1
  • Svitlana Zinger
    • 1
  • Peter H. N. de With
    • 1
  1. 1.Eindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Philips ResearchEindhovenThe Netherlands

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