A scalable computational approach to assessing response to name in toddlers with autism

Abstract

This study is part of a larger research program focused on developing objective, scalable tools for digital behavioral phenotyping. We evaluated whether a digital app delivered on a smartphone or tablet using computer vision analysis (CVA) can elicit and accurately measure one of the most common early autism symptoms, namely failure to respond to a name call.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 28, 2021
Source ID
10.1111/jcpp.13381

Entities

People

  • Adrianne Harris
  • Barbara Walter
  • Brian Eichner
  • Eliana M. Perrin
  • Geraldine Dawson
  • Guillermo Sapiro
  • Jacqueline Flowers
  • Jeffrey Baker
  • Jill Howard
  • Kimberly Carpenter
  • Lauren Franz
  • Marina Spanos
  • Martha Gagliano
  • Matias Di Martino
  • Naomi Davis
  • Pradeep Raj
  • Rachel Aiello
  • Sam Perochon
  • Scott Compton
  • Scott H. Kollins
  • Steven Espinosa
  • Zhuoqing Chang

Organizations

  • Duke University
  • Office of Naval Research

Tags

Readers

  • Aerospace Test and Evaluation
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Child and Adolescent Substance Abuse Science in Autism Spectrum Disorders.

Technology Areas

  • AI & ML