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Behaviour patterns detection for persuasive design in Nursing Homes to help dementia patients

机译:护理家庭有说服力设计的行为模式检测,帮助痴呆症患者

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Nursing homes usually host large accounts of persons with different levels of dementia. Detecting dementia process in early stages may allow the application of mechanisms to reduce or stop the cognitive impairment. Our ultimate objective is to demonstrate that the use of persuasive techniques may serve to motivate these subjects and induct re-learning mechanisms to stop mental impairment. Nevertheless, this requires the study of the behaviour of each patient individually in order to detect conduct disorders in their living ambient. This study presents a behavior pattern detection architecture based on the Ambient Assisted Living paradigm and Workflow Mining technology to enable re-learning mechanisms in dementia processes via providing tools to automate the conduct disorder detection. This architecture fosters the use of Workflows as representation languages to allow health professionals to represent persuasive motivation protocols in the AAL environment to react individually to dementia symptoms detected.
机译:护理家庭通常举办大量痴呆症的人。检测早期阶段的痴呆过程可以允许应用机制来减少或阻止认知障碍。我们的终极目标是证明使用说服技术的使用可能有助于激励这些科目,并归功于抵抗精神障碍的重新学习机制。然而,这需要单独研究每位患者的行为,以便在其生活环境中检测到的导尿。本研究提出了一种基于环境辅助生活范式和工作流挖掘技术的行为模式检测架构,通过提供自动化导电病症检测的工具来实现痴呆症过程中的重新学习机制。该体系结构促进了使用工作流作为表示语言,以允许健康专业人员代表AAL环境中的有说服力的动机协议,以单独对检测到的痴呆症状作出反应。

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