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Quantified Living Habits Using RTI Based Target Footprint Data

机译:使用基于RTI的目标足迹数据量化生活习惯

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Providing personalized healthcare for elders is more and more necessary in aging society. It is the premise to quantify their living habits properly. In this paper, a classification algorithm is used to transform footprints of elder into daily activities by combining point of interest. A concept of activity matrix and vector is proposed to quantify daily life, and then a clustering algorithm based on similarity is put forward to realize abnormal behaviors recognition. Finally, a experiment is given to illustrate the effectiveness of the proposed methods.
机译:在老龄化社会中,为老年人提供个性化医疗保健变得越来越必要。正确地量化他们的生活习惯是前提。本文采用分类算法,通过结合兴趣点将老年人的足迹转化为日常活动。提出了一种活动矩阵和向量的概念来量化日常生活,然后提出了一种基于相似度的聚类算法来实现对异常行为的识别。最后,通过实验说明了所提方法的有效性。

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