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Collecting big behavioral data for measuring behavior against obesity

机译:收集大的行为数据以衡量针对肥胖的行为

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Obesity is currently affecting very large portions of the global population. Effective prevention and treatment starts at the early age and requires objective knowledge of population-level behavior on the regioneighborhood scale. To this end, we present a system for extracting and collecting behavioral information on the individual-level objectively and automatically. The behavioral information is related to physical activity, types of visited places, and transportation mode used between them. The system employs indicator-extraction algorithms from the literature which we evaluate on publicly available datasets. The system has been developed and integrated in the context of the EU-funded BigO project that aims at preventing obesity in young populations.
机译:肥胖症目前正在影响全球人口的很大一部分。有效的预防和治疗始于早期,需要客观地了解区域/邻里范围内的人口行为。为此,我们提出了一种客观,自动地提取和收集个人行为信息的系统。行为信息与体育活动,探访地点的类型以及它们之间使用的运输方式有关。该系统采用了文献中的指标提取算法,我们对可公开获得的数据集进行了评估。该系统是在欧盟资助的旨在防止年轻人肥胖的BigO项目的背景下开发和集成的。

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