Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/716990
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dc.contributor.authorHaibin Cai|Yinfeng Fang|Zhaojie Ju|Cristina Costescu|Daniel David|Erik Billing|Tom Ziemke|Serge Thill|Tony Belpaeme|Bram Vanderborght|David Vernon|Kathleen Richardson|Honghai Liuen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:32Z-
dc.date.available2021-05-16T17:43:32Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877662en_US
dc.identifier.urihttp://localhost/handle/Hannan/716990-
dc.description.abstractIt is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features, such as body motion features, facial expressions, and gaze features, further assessing the children behaviors by mapping them to therapist-specified behavioral classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behavior assessment.en_US
dc.relation.haspart08502783.pdfen_US
dc.subjecttherapy|autonomy|Sensing-enhanced|autism spectrum disordersen_US
dc.titleSensing-Enhanced Therapy System for Assessing Children With Autism Spectrum Disorders: A Feasibility Studyen_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

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dc.contributor.authorHaibin Cai|Yinfeng Fang|Zhaojie Ju|Cristina Costescu|Daniel David|Erik Billing|Tom Ziemke|Serge Thill|Tony Belpaeme|Bram Vanderborght|David Vernon|Kathleen Richardson|Honghai Liuen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:32Z-
dc.date.available2021-05-16T17:43:32Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877662en_US
dc.identifier.urihttp://localhost/handle/Hannan/716990-
dc.description.abstractIt is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features, such as body motion features, facial expressions, and gaze features, further assessing the children behaviors by mapping them to therapist-specified behavioral classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behavior assessment.en_US
dc.relation.haspart08502783.pdfen_US
dc.subjecttherapy|autonomy|Sensing-enhanced|autism spectrum disordersen_US
dc.titleSensing-Enhanced Therapy System for Assessing Children With Autism Spectrum Disorders: A Feasibility Studyen_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502783.pdf3.59 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHaibin Cai|Yinfeng Fang|Zhaojie Ju|Cristina Costescu|Daniel David|Erik Billing|Tom Ziemke|Serge Thill|Tony Belpaeme|Bram Vanderborght|David Vernon|Kathleen Richardson|Honghai Liuen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:32Z-
dc.date.available2021-05-16T17:43:32Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877662en_US
dc.identifier.urihttp://localhost/handle/Hannan/716990-
dc.description.abstractIt is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features, such as body motion features, facial expressions, and gaze features, further assessing the children behaviors by mapping them to therapist-specified behavioral classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behavior assessment.en_US
dc.relation.haspart08502783.pdfen_US
dc.subjecttherapy|autonomy|Sensing-enhanced|autism spectrum disordersen_US
dc.titleSensing-Enhanced Therapy System for Assessing Children With Autism Spectrum Disorders: A Feasibility Studyen_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502783.pdf3.59 MBAdobe PDFThumbnail
Preview File