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Mining for Patterns of Behaviour in Children with Autism Through Smartphone Technology

机译:通过智能手机技术挖掘自闭症儿童的行为模式

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A requirement to maintain detailed recording of child behaviour is commonplace for families engaged in home-based autism intervention therapy. Periodically, a Behaviour Analyst reviews this data to formulate new behaviour change plans and as such, the quality and accuracy of data is paramount. We present a smartphone application that aims to streamline the traditional paper based approaches, which are prone to non-compliance and erroneous detail. In addition, we have applied association rule mining to the collected behaviour data to extract patterns in terms of behaviour causes and effects with a view to offer intelligent support to the Behaviour Analysts when formulating new interventions. The paper oudines the results of a small evaluation of the smartphone component before introducing the methodology used to mine that data to highlight behaviour rules and patterns. Consequently, based on an initial sample of child behaviours, the methodology is then compared to a Behaviour Analyst's assessment of corresponding paper based records.
机译:对从事家庭自闭症干预治疗的家庭来说,保持详细记录儿童行为的要求是司空见惯的。行为分析师会定期检查此数据以制定新的行为更改计划,因此,数据的质量和准确性至关重要。我们提供了一款智能手机应用程序,旨在简化传统的基于纸张的方法,这些方法容易出现违规和错误的细节。此外,我们将关联规则挖掘应用于收集的行为数据,以从行为因果角度提取模式,以期在制定新干预措施时为行为分析师提供智能支持。在介绍用于挖掘数据以突出显示行为规则和模式的方法之前,本文将对智能手机组件进行一次小型评估的结果。因此,基于儿童行为的初始样本,然后将该方法与行为分析师对相应纸质记录的评估进行比较。

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