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概念开发与应用:自动化食物摄入和饮食行为评估方法

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method.

机构信息

Division of Human Nutrition and Health, Wageningen University & Research;

Division of Human Nutrition and Health, Wageningen University & Research.

出版信息

J Vis Exp. 2021 Feb 19(168). doi: 10.3791/62144.

DOI:10.3791/62144
PMID:33682853
Abstract

The vast majority of dietary and eating behavior assessment methods are based on self-reports. They are burdensome and also prone to measurement errors. Recent technological innovations allow for the development of more accurate and precise dietary and eating behavior assessment tools that require less effort for both the user and the researcher. Therefore, a new sensor-based device to assess food intake and eating behavior was developed. The device is a regular dining tray equipped with a video camera and three separate built-in weighing stations. The weighing stations measure the weight of the bowl, plate, and drinking cup continuously over the course of a meal. The video camera positioned to the face records eating behavior characteristics (chews, bites), which are analyzed using artificial intelligence (AI)-based automatic facial expression software. The tray weight and the video data are transported at real-time to a personal computer (PC) using a wireless receiver. The outcomes of interest, such as the amount eaten, eating rate and bite size, can be calculated by subtracting the data of these measures at the timepoints of interest. The information obtained by the current version of the tray can be used for research purposes, an upgraded version of the device would also facilitate the provision of more personalized advice on dietary intake and eating behavior. Contrary to the conventional dietary assessment methods, this dietary assessment device measures food intake directly within a meal and is not dependent on memory or the portion size estimation. Ultimately, this device is therefore suited for daily main meal food intake and eating behavior measures. In the future, this technology based dietary assessment method can be linked to health applications or smart watches to obtain a complete overview of exercise, energy intake, and eating behavior.

摘要

绝大多数饮食和进食行为评估方法都是基于自我报告的。这些方法既繁琐又容易产生测量误差。最近的技术创新使得开发更准确、更精确的饮食和进食行为评估工具成为可能,这些工具既减少了用户的工作量,也减少了研究人员的工作量。因此,我们开发了一种新的基于传感器的设备来评估食物摄入量和进食行为。该设备是一个普通的餐盘,配有摄像头和三个独立的内置称重台。称重台在整个用餐过程中连续测量碗、盘子和杯子的重量。位于餐盘正上方的摄像头记录进食行为特征(咀嚼、咬),这些特征使用基于人工智能(AI)的自动面部表情软件进行分析。托盘重量和视频数据通过无线接收器实时传输到个人计算机(PC)。通过减去特定时间点的这些测量数据,可以计算出感兴趣的结果,例如摄入量、进食速度和咬口大小。当前版本的托盘可以用于研究目的,而设备的升级版本还将有助于提供更个性化的饮食摄入和进食行为建议。与传统的饮食评估方法不同,这种饮食评估设备直接在餐中测量食物摄入量,不依赖于记忆或食物份量估计。因此,该设备非常适合日常主餐的食物摄入量和进食行为测量。将来,这种基于技术的饮食评估方法可以与健康应用程序或智能手表结合使用,以全面了解运动、能量摄入和进食行为。

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