Screening Early Children With Autism Spectrum Disorder via Response-to-Name Protocol

Incidence of children with autism spectrum disorder (ASD) has increased with an average rate of 1% worldwide. Clinical ASD screening, especially for children screening is a laborious and skilled task; however, there is no objective and effective method automating ASD children screening. Analyzing ch...

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Veröffentlicht in:IEEE transactions on industrial informatics Jg. 17; H. 1; S. 587 - 595
Hauptverfasser: Wang, Zhiyong, Liu, Jingjing, He, Keshi, Xu, Qiong, Xu, Xiu, Liu, Honghai
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Autism
Autism spectrum disorder (ASD)
Autistic children
Automation
Cameras
Computer vision
early screening
Estimation
gaze estimation
Head
multisensor fusion
Pediatrics
Protocols
response to name (RTN)
Screening
ISSN:1551-3203, 1941-0050
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Zusammenfassung:Incidence of children with autism spectrum disorder (ASD) has increased with an average rate of 1% worldwide. Clinical ASD screening, especially for children screening is a laborious and skilled task; however, there is no objective and effective method automating ASD children screening. Analyzing children ASD characteristics in predefined motion behavior protocols is attempted to provide automatic solutions to children ASD screening. A novel protocol, response to name (RTN), is proposed in this article for ASD clinical validation and diagnosis. The RTN method is jointly designed with clinical partners, and novel gaze estimation is developed for validating ASD characteristic behavior. Seventeen subjects including ten adults and seven children (five ASD subjects and two healthy subjects) have participated the experiment. The experiment results show that the proposed RTN system achieves an average classification score of 92.7% fully demonstrating that the principle of motion protocol based ASD screening has the potential to have early ASD screening automated.
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2019.2958106