收集大量行为数据以衡量肥胖行为
Collecting big behavioral data for measuring behavior against obesity
摘要：
肥胖目前影响着全球人口的很大一部分。有效的预防和治疗从幼年开始，需要对区域/邻里规模的人口行为有客观的了解。为此，我们提出了一个系统，用于提取和收集个人层面上的行为信息的客观和自动。行为信息与身体活动，访问的地方类型以及它们之间使用的交通方式有关。该系统采用的指标提取算法，从文献中，我们评估公开可用的数据集。该系统是在欧盟资助的BigO项目的背景下开发和整合的，该项目旨在预防年轻人的肥胖。
英文摘要：
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 region/neighborhood 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
