CGMacros: a scientific dataset for personalized nutrition and diet monitoring
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We present CGMacros, a dataset containing multimodal information from two continuous glucose monitors (CGM), food macronutrients, food photographs, and physical activity, in addition to anonymized participant demographics, anthropometric measurements and health parameters from blood analyses and gut microbiome profiles. CGMacros contains data from 45 study participants (15 healthy adults, 16 with pre-diabetes, and 14 with Type 2 diabetes) who consumed meals with varying and known macronutrient compositions in a free- living setting for ten consecutive days. To our knowledge, this is the first database of its kind to be made publicly available. CGMacros, and larger publicly available datasets that we hope may follow, are essential to democratize academic research in personalized nutrition and algorithmic approaches to automated diet monitoring.
本研究提出CGMacros数据集,该数据集包含来自两台连续血糖监测仪(Continuous Glucose Monitor, CGM)、食物宏量营养素、食物图像以及身体活动的多模态信息,同时涵盖匿名化的受试者人口统计学资料、人体测量学指标,以及通过血液分析与肠道微生物组谱获取的健康参数。CGMacros的数据集来自45名研究受试者,其中15名为健康成年人,16名处于糖尿病前期,14名患有2型糖尿病;所有受试者在连续十天的自由生活环境中食用了宏量营养素组成各异且已知的餐食。据我们所知,这是首个公开可用的同类型数据库。CGMacros以及我们期待后续推出的更大规模公开数据集,对于推动个性化营养领域的学术研究与自动化饮食监测算法方法的普及至关重要。




