Doulah Abul, McCrory Megan A, Higgins Janine A, Sazonov Edward
Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.
Department of Health Sciences, Boston University, MA 02215, USA.
IEEE Access. 2019;7:49653-49668. doi: 10.1109/access.2019.2910308. Epub 2019 Apr 11.
Accurate measurement of energy intake (EI) is important for estimation of energy balance, and, correspondingly, body weight dynamics. Traditional measurements of EI rely on self-report, which may be inaccurate and underestimate EI. The imperfections in traditional methodologies such as 24-hour dietary recall, dietary record, and food frequency questionnaire stipulate development of technology-driven methods that rely on wearable sensors and imaging devices to achieve an objective and accurate assessment of EI. The aim of this research was to systematically review and examine peer-reviewed papers that cover the estimation of EI in humans, with the focus on emerging technology-driven methodologies. Five major electronic databases were searched for articles published from January 2005 to August 2017: Pubmed, Science Direct, IEEE Xplore, ACM library, and Google Scholar. Twenty-six eligible studies were retrieved that met the inclusion criteria. The review identified that while the current methods of estimating EI show promise, accurate estimation of EI in free-living individuals presents many challenges and opportunities. The most accurate result identified for EI (kcal) estimation had an average accuracy of 94%. However, collectively, the results were obtained from a limited number of food items (i.e., 19), small sample sizes (i.e., 45 meal images), and primarily controlled conditions. Therefore, new methods that accurately estimate EI over long time periods in free-living conditions are needed.
准确测量能量摄入（EI）对于评估能量平衡以及相应的体重动态变化至关重要。传统的EI测量方法依赖自我报告，这可能不准确且会低估EI。诸如24小时饮食回顾、饮食记录和食物频率问卷等传统方法存在缺陷，这就需要开发基于可穿戴传感器和成像设备的技术驱动方法，以实现对EI的客观准确评估。本研究的目的是系统回顾和审视同行评审的论文，这些论文涵盖了人类EI的估计，重点是新兴的技术驱动方法。在五个主要电子数据库中搜索了2005年1月至2017年8月发表的文章：PubMed、Science Direct、IEEE Xplore、ACM图书馆和谷歌学术。检索到26项符合纳入标准的合格研究。该综述指出，虽然当前估计EI的方法显示出前景，但在自由生活个体中准确估计EI仍面临诸多挑战和机遇。EI（千卡）估计的最准确结果平均准确率为94%。然而，总体而言，这些结果是从有限数量的食物项目（即19种）、小样本量（即45张膳食图像）以及主要是受控条件下获得的。因此，需要新的方法来在自由生活条件下长时间准确估计EI。
