RoDiCA: a human-robot interaction system for treatment of childhood autism spectrum disorders
RoDiCA: a human-robot interaction system for treatment of childhood autism spectrum disorders
复制标题
RoDiCA：用于治疗儿童自闭症谱系障碍的人机交互系统
DOI：
10.1145/2413097.2413160
复制
发表时间：
2012
影响因子：
4.6
通讯作者：
D. Popa
中科院分区：
文献类型：
--
作者：
I. Ranatunga;Nahum A. Torres;R. Patterson;N. Bugnariu;M. Stevenson;D. Popa
在本文中，我们描述了在虚拟环境中实现交互式机器人技术，以完成人机交互以治疗自闭症谱系障碍（ASD）。我们的系统与患有自闭症谱系障碍的儿童之间的互动是通过教他们的肢体语言来完成的，例如手和手臂的动作、面部表情和言语，以鼓励他们与其他人进行社交互动并提高他们的运动技能。 Kinect 传感器用于允许治疗师或儿童直接控制人形机器人 Zeno，以实现动态交互。动作捕捉系统同时记录芝诺和孩子的动作，以评估互动。具体来说，我们比较孩子的手臂和躯干运动，这些运动应该紧密跟随机器人的运动。这种行为可用于机器人辅助治疗期间的临床治疗和诊断。治疗师可以利用这种交互行为来实现机器人所需的姿势，这可能有利于患有自闭症谱系障碍的儿童增强他们的运动技能和社交互动技能。为了比较机器人和受试者的运动特征，我们使用了各种指标，例如互相关和信号 2-范数。结果表明，儿童的运动紧密跟随机器人的运动，分析技术是比较人类和机器人运动相似性的合理指标。
In this paper, we describe the implementation of interactive robotics in virtual environments accomplishing human-robot interaction for treatment of Autism Spectrum Disorders (ASDs). Interaction between our system and children suffering from ASDs is accomplished by teaching them body language such as hand and arm motion, facial expressions and speech to encourage them to engage in social interaction with other humans and for improving their motor skills. A Kinect sensor is used to allow direct control of the humanoid robot, Zeno, by the therapist or child to enable dynamic interaction. The motions of Zeno and the child are recorded simultaneously by a motion capture system to assess the interaction. Specifically, we compare arm and torso motions of the child which should closely follow those of the robot. This behavior can be used for clinical treatment and diagnosis during robot assisted therapy. Therapists can take advantage of this interactive behavior to achieve desired poses of the robot that may be beneficial to children with ASDs to enhance their motor skills as well as their social interaction skills. In order to compare the motion characteristics of robots and subjects, we use various metrics such as cross correlation and signal 2-norm. Results show that the child's motion follows the robot's motion closely and the analysis techniques are reasonable indicators to compare the similarity of the human and robot motions.