Feasibility of Using Wearable Sensors and Artificial Intelligence for Carbohydrate Counting in Chinese Americans with Type 2 Diabetes

Brief description of study

The purpose of this research study is to evaluate the accuracy and acceptability of using eButton for carbohydrate counting in Chinese Americans who have type 2 diabetes (T2D). The eButton is a wearable camera (pinned near your upper chest) that is about the third of the size of a credit card and used to automatically record information about the food you consume during a meal. The recorded food picture data from eButton are processed by the artificial intelligence technology to automatically determine food names, volumes, and nutrient values (like grams of carbohydrates) of the food you eat. Usually, people with Type 2 Diabetes who count carbohydrates to maintain control of their blood sugar measure food portions, keep a food diary, and calculate their carbohydrate intake, which can be inaccurate, challenging, and burdensome.


Clinical Study Identifier: s21-01714
Principal Investigator: Yaguang Zheng.


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