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促进儿童肥胖健康:基于数据自我追踪的方法。

Health Promotion for Childhood Obesity: An Approach Based on Self-Tracking of Data.

机构信息

Grupo GRIAL, Instituto Universitario de Ciencias de la Educación, Universidad de Salamanca; Paseo de Canalejas, 169, 37008 Salamanca, Spain.

Grupo ITED, Computer Engineering and Systems Department, Universidad de La Laguna; Avda. Astrofísico Sánchez s/n, Physics and Mathematics Building, La Laguna, 38204 Tenerife, Spain.

出版信息

Sensors (Basel). 2020 Jul 6;20(13):3778. doi: 10.3390/s20133778.

Abstract

At present, obesity and overweight are a global health epidemic. Traditional interventions for promoting healthy habits do not appear to be effective. However, emerging technological solutions based on wearables and mobile devices can be useful in promoting healthy habits. These applications generate a considerable amount of tracked activity data. Consequently, our approach is based on the quantified-self model for recommending healthy activities. Gamification can also be used as a mechanism to enhance personalization, increasing user motivation. This paper describes the quantified-self model and its data sources, the activity recommender system, and the PROVITAO App user experience model. Furthermore, it presents the results of a gamified program applied for three years in children with obesity and the process of evaluating the quantified-self model with experts. Positive outcomes were obtained in children's medical parameters and health habits.

摘要

目前,肥胖和超重是一种全球健康流行病。传统的促进健康习惯的干预措施似乎并不有效。然而,基于可穿戴设备和移动设备的新兴技术解决方案在促进健康习惯方面可能很有用。这些应用程序会生成大量可追踪的活动数据。因此,我们的方法基于量化自我模型来推荐健康活动。游戏化也可以用作增强个性化、提高用户积极性的机制。本文描述了量化自我模型及其数据源、活动推荐系统和 PROVITAO App 用户体验模型。此外,还介绍了在肥胖儿童中应用三年的游戏化计划的结果,以及与专家一起评估量化自我模型的过程。在儿童的医疗参数和健康习惯方面取得了积极的成果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb05/7374452/933cf9666909/sensors-20-03778-g001.jpg

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