Merging dietary assessment with the adolescent lifestyle.

Merging dietary assessment with the adolescent lifestyle.
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DOI:
10.1111/jhn.12071
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发表时间:
2014-01
期刊:
Journal of human nutrition and dietetics : the official journal of the British Dietetic Association
影响因子:
--
通讯作者:
Boushey CJ
Boushey CJ
中科院分区:
其他
文献类型:
--
作者:
Schap TE;Zhu F;Delp EJ;Boushey CJ

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基于图像的饮食评估方法的使用显示出改善儿童饮食自我报告的前景。技术辅助饮食评估(TADA)食品记录应用程序是一种自我管理的食品记录,专门设计用于解决与传统饮食评估方法相关的负担和人为错误。用户可以使用移动电话或带有集成摄像头的移动设备(例如,Apple iPhone、Google Nexus One、Apple iPod Touch)在所有进食场合拍摄食物和饮料的图像。一旦拍摄了图像,图像就被传输到后端服务器进行自动分析。这一过程的第一步是图像分析,即分割、特征提取和分类,允许自动识别食物。通过分割和几何形状模板建模,还可以自动估计部分大小。自动食物识别和体积估计的结果可以与饮食研究的食物和营养数据库(FNDDS)一起编入索引,以提供详细的饮食分析,用于流行病学或干预研究。在类似营地的环境中进行受控喂养研究期间收集的数据已允许对TADA食品记录应用程序进行形成性评估和验证。本文综述了基于图像的儿童膳食评估方法的系统设计和循证发展。
The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera, (e.g., Apple iPhone, Google Nexus One, Apple iPod Touch). Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis, i.e., segmentation, feature extraction, and classification, allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies (FNDDS) to provide a detailed diet analysis for use in epidemiologic or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarizes the system design and the evidence-based development of image-based methods for dietary assessment among children.
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