Defining and distinguishing infant behavioral states using acoustic cry analysis: is colic painful?

Journal: Pediatric research
PMID: 31585457

Abstract

BACKGROUND: To characterize acoustic features of an infant's cry and use machine learning to provide an objective measurement of behavioral state in a cry-translator. To apply the cry-translation algorithm to colic hypothesizing that these cries sound painful.

Authors

  • Joanna J Parga
    Children's Hospital of Pennsylvania, Philadelphia, PA, USA.
  • Sharon Lewin
    David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
  • Juanita Lewis
    David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
  • Diana Montoya-Williams
    Children's Hospital of Pennsylvania, Philadelphia, PA, USA.
  • Abeer Alwan
    University of California, Los Angeles, CA, USA.
  • Brianna Shaul
    Private Practice, Los Angeles, CA, USA.
  • Carol Han
    University of California, Los Angeles, CA, USA.
  • Susan Y Bookheimer
    University of California, Los Angeles, CA, USA.
  • Sherry Eyer
    Gallaudet University, Washington, DC, USA.
  • Mirella Dapretto
    University of California, Los Angeles, CA, USA.
  • Lonnie Zeltzer
    David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
  • Lauren Dunlap
    University of California, Los Angeles, CA, USA.
  • Usha Nookala
    University of California, Los Angeles, CA, USA.
  • Daniel Sun
    University of California, Los Angeles, CA, USA.
  • Bianca H Dang
    University of California, Los Angeles, CA, USA.
  • Ariana E Anderson
    University of California, Los Angeles, CA, USA. ariana82@ucla.edu.

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