论文标题
使用平淡的视频对青少年和年轻人的基于目光的自闭症检测
Gaze-based Autism Detection for Adolescents and Young Adults using Prosaic Videos
论文作者
论文摘要
自闭症通常在青少年和成年人中仍未诊断。先前的研究表明，自闭症个体通常会显示出非典型的固定和凝视模式。在这篇简短的论文中，我们证明，通过监视用户观看司空见惯（即不是专业，结构化或编码）视频时的目光，我们可以识别患有自闭症谱系障碍的人。我们招募了35名自闭症和25个非自动人物的人，并使用与笔记本电脑相连的现成的眼动仪捕捉了他们的目光。在15秒钟内，我们的方法在识别自闭症诊断的个体方面准确92.5％。我们设想在网络媒体的消耗过程中应用此类自动检测，这可以允许对用户界面进行被动筛查和适应。
Autism often remains undiagnosed in adolescents and adults. Prior research has indicated that an autistic individual often shows atypical fixation and gaze patterns. In this short paper, we demonstrate that by monitoring a user's gaze as they watch commonplace (i.e., not specialized, structured or coded) video, we can identify individuals with autism spectrum disorder. We recruited 35 autistic and 25 non-autistic individuals, and captured their gaze using an off-the-shelf eye tracker connected to a laptop. Within 15 seconds, our approach was 92.5% accurate at identifying individuals with an autism diagnosis. We envision such automatic detection being applied during e.g., the consumption of web media, which could allow for passive screening and adaptation of user interfaces.
