Data Quality as a Bottleneck in Developing a Social-Serious-Game-Based Multi-modal System for Early Screening for 'High Functioning' Cases of Autism Spectrum Condition

被引：5

作者：

Gyori, Miklos ^{[1
]}

Borsos, Zsofia ^{[1
]}

Stefanik, Krisztina ^{[2
]}

Csakvari, Judit ^{[1
]}

机构：

[1] ELTE Univ, Inst Psychol Special Needs, Budapest, Hungary

[2] ELTE Univ, Inst Special Educ Atyp Cognit & Behav, Budapest, Hungary

来源：

COMPUTERS HELPING PEOPLE WITH SPECIAL NEEDS, PT II (ICCHP 2016) | 2016年 / 9759卷

关键词：

Autism spectrum condition; Data quality; Emotional facial expression; Eye tracking; Screening; Serious game; DIAGNOSIS;

D O I：

10.1007/978-3-319-41267-2_51

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Our aim is to explore raw data quality in the first evaluation of the first fully playable prototype of a social-serious-game-based, multi-modal, interactive software system for screening for high functioning cases of autism spectrum condition at kindergarten age. Data were collected from 10 high functioning children with autism spectrum condition and 10 typically developing children. Mouse and eye-tracking data, and data from automated emotional facial expression recognition were analyzed quantitatively. Results show a sub-optimal level of raw data quality and suggest that it is a bottleneck in developing screening/diagnostic/assessment tools based on multi-mode behavioral data.

引用

页码：358 / 366

页数：9