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The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy
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 child...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444515/ https://www.ncbi.nlm.nih.gov/pubmed/32823270 http://dx.doi.org/10.1371/journal.pone.0236939 |
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author | Billing, Erik Belpaeme, Tony Cai, Haibin Cao, Hoang-Long Ciocan, Anamaria Costescu, Cristina David, Daniel Homewood, Robert Hernandez Garcia, Daniel Gómez Esteban, Pablo Liu, Honghai Nair, Vipul Matu, Silviu Mazel, Alexandre Selescu, Mihaela Senft, Emmanuel Thill, Serge Vanderborght, Bram Vernon, David Ziemke, Tom |
author_facet | Billing, Erik Belpaeme, Tony Cai, Haibin Cao, Hoang-Long Ciocan, Anamaria Costescu, Cristina David, Daniel Homewood, Robert Hernandez Garcia, Daniel Gómez Esteban, Pablo Liu, Honghai Nair, Vipul Matu, Silviu Mazel, Alexandre Selescu, Mihaela Senft, Emmanuel Thill, Serge Vanderborght, Bram Vernon, David Ziemke, Tom |
author_sort | Billing, Erik |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7444515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74445152020-08-27 The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy Billing, Erik Belpaeme, Tony Cai, Haibin Cao, Hoang-Long Ciocan, Anamaria Costescu, Cristina David, Daniel Homewood, Robert Hernandez Garcia, Daniel Gómez Esteban, Pablo Liu, Honghai Nair, Vipul Matu, Silviu Mazel, Alexandre Selescu, Mihaela Senft, Emmanuel Thill, Serge Vanderborght, Bram Vernon, David Ziemke, Tom PLoS One Research Article 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. Public Library of Science 2020-08-21 /pmc/articles/PMC7444515/ /pubmed/32823270 http://dx.doi.org/10.1371/journal.pone.0236939 Text en © 2020 Billing et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Billing, Erik Belpaeme, Tony Cai, Haibin Cao, Hoang-Long Ciocan, Anamaria Costescu, Cristina David, Daniel Homewood, Robert Hernandez Garcia, Daniel Gómez Esteban, Pablo Liu, Honghai Nair, Vipul Matu, Silviu Mazel, Alexandre Selescu, Mihaela Senft, Emmanuel Thill, Serge Vanderborght, Bram Vernon, David Ziemke, Tom The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
title | The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
title_full | The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
title_fullStr | The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
title_full_unstemmed | The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
title_short | The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
title_sort | dream dataset: supporting a data-driven study of autism spectrum disorder and robot enhanced therapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444515/ https://www.ncbi.nlm.nih.gov/pubmed/32823270 http://dx.doi.org/10.1371/journal.pone.0236939 |
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