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首页> 外文会议>Human Factors and Ergonomics Society annual meeting >EXPLORING CHALLENGES OF MONITORING TECHNOLOGY AND SELF-INJURIOUS BEHAVIOR IN AUTISM SPECTRUM DISORDER
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EXPLORING CHALLENGES OF MONITORING TECHNOLOGY AND SELF-INJURIOUS BEHAVIOR IN AUTISM SPECTRUM DISORDER

机译：探讨自闭症谱系障碍监测技术及自我伤害行为的挑战

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摘要

Self-injurious behavior (SIB), such as head banging orself-hitting, is considered one of the most dangerouscharacteristics of autism spectrum disorder (ASD) (Mahatmya,Zobel, & Valdovinos, 2008). Clinicians traditionally rely onstructured observation, which can be time-consuming andinvasive. Recent technological developments in motiontracking may decrease these burdens. For example,accelerometers in smart watches can gather movementinformation, which could be automatically classified to detectand predict events associated with SIB using machine learningalgorithms. While such systems have clear potential toobjectively, accurately, and efficiently monitor and predictSIB, this potential will not be fully realized unless devices areadopted and integrated into clinics and homes.
机译：自我伤害的行为（SIB），如头部撞击或自打，被认为是最危险的自闭症谱系障碍（ASD）的特征（Mahatmya，Zobel，＆Valdovinos，2008）。临床医生传统上依赖结构化观察，这可能是耗时的侵入性。最近的动作技术发展跟踪可能会降低这些负担。例如，智能手表的加速度计可以收集运动信息，可以自动分类以检测并预测使用机器学习与SIB相关的事件算法。虽然这种系统具有明显的潜力客观，准确，有效地监控和预测除非设备是，否则这些潜力不会完全实现采用并融入诊所和家庭。

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