在玩游戏时评估自闭症程度

Sridari Iyer, Rupesh Mishra, Snehal P. Kulkami, D. Kalbande
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引用次数: 6

摘要

自闭症是一种学习障碍,属于ADHD(注意缺陷多动障碍)谱系,从轻微自闭症到严重自闭症不等。自闭症的程度是由一位特殊的教育工作者在仔细检查孩子的活动后判断的。本文提出了一种算法,可以使这一评估过程自动化。当玩家在玩游戏时,他们的活动模式就会被捕捉到。这被解释为定义玩家运动技能、认知能力和焦虑水平的参数。它们一起被分析,并使用模糊逻辑计算出玩家的自闭症水平。这些参数可以使用无监督学习算法进行细化,以呈现更准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assess autism level while playing games
Autism is a learning disorder falling in the ADHD (Attention Deficit Hyperactivity Disorder) spectrum, varying from being slightly autistic to severe. The level of autism is judged by a special educator after close examination of the child's activities. This paper presents an algorithm that can automate this assessing procedure. While a game is being played the activity pattern of the player is captured in the background. This is interpreted into parameters that define the player's motor skills, cognitive power and anxiety level. Together they are analyzed and the player's level of autism is calculated using fuzzy logic. These parameters can be refined using an unsupervised learning algorithm to render more accurate results.
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