PLoS ONE (Jan 2020)

The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy.

  • Erik Billing,
  • Tony Belpaeme,
  • Haibin Cai,
  • Hoang-Long Cao,
  • Anamaria Ciocan,
  • Cristina Costescu,
  • Daniel David,
  • Robert Homewood,
  • Daniel Hernandez Garcia,
  • Pablo Gómez Esteban,
  • Honghai Liu,
  • Vipul Nair,
  • Silviu Matu,
  • Alexandre Mazel,
  • Mihaela Selescu,
  • Emmanuel Senft,
  • Serge Thill,
  • Bram Vanderborght,
  • David Vernon,
  • Tom Ziemke

DOI
https://doi.org/10.1371/journal.pone.0236939
Journal volume & issue
Vol. 15, no. 8
p. e0236939

Abstract

Read online

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children's behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general.