Paper Info
Title
An EEG-based Adaptive Training System for ASD Children.
Abstract
Children with ASD (Autism Spectrum Disorder) have difficulties in expressing their feelings and needs, their teachers have to be very familiar with them to adjust teaching contents in related training lessons. In this paper, we present an adaptive training system with EEG (Electroencephalogram) devices for autistic children. We designed an EEG helmet to monitor children's attention levels, and a video chat system with virtual cartoon faces covered on teacher's face. Cartoon faces are synchronized with the performer's facial movements to help trainers express themselves in an exaggerated way. When the attention reduction is detected by the EEG helmet, cartoon face will adjust automatically, and try to draw their attention back through changing cartoon types, colors, brightness, etc. Each change and feedback from children will be traced by the helmet and analyzed for improvements. By continuous iterative learning, the system will become smarter in avoiding children's physical exhaustion. The system was introduced in the form of a specific training lesson to an ASD school, and preliminary experiment has indicated an encouraging result.
Year
DOI
Venue
2017
10.1145/3131785.3131832
UIST '17: The 30th Annual ACM Symposium on User Interface Software and Technology Québec City QC Canada October, 2017
Keywords
Field
DocType
EEG, ASD, Children education, Augmented Reality, Iterative Learning
Physical exhaustion,Computer science,Training system,Augmented reality,Human–computer interaction,Iterative learning control,Autism spectrum disorder,Multimedia,Feeling,Electroencephalography
Conference
ISBN
Citations 
PageRank 
978-1-4503-5419-6
0
0.34
References 
Authors
4
9
Name
Order
Citations
PageRank
Cheng Zheng131.66
Caowei Zhang2123.44
Xuan Li312427.25
Bing Li401.35
Fan Zhang522969.82
Xin Liu628774.92
Cheng Yao700.68
Yijun Zhao836.46
Fangtian Ying9186.64