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在可穿戴传感器系统中评估食品份量大小的盘子和碗尺寸的估计

Viprav B Raju¹, Delwar Hossain¹, Edward Sazonov¹

¹Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35401 USA.

IEEE sensors journal

|October 6, 2023

概括

这项研究引入了一种可穿戴式传感器系统,用于自动估计食品份量大小 (FPSE). 这种新方法准确地测量容器尺寸,无需用户交互或参考标记.

科学领域:

生物医学工程生物医学工程
计算机视觉计算机视觉
人与计算机的交互

背景情况:

自动食品份量大小估计 (FPSE) 是具有极小用户负担的挑战.
目前的FPSE方法通常依赖于信托标记或虚拟模型来进行维度引用.
估计食用容器尺寸是FPSE的一个可行的替代方法.

研究的目的:

提出一种可穿戴的传感器系统和估计盘子和碗尺寸的方法.
为了实现精确的FPSE与最小的用户交互.
克服现有的FPSE技术的局限性.

主要方法:

开发一个可穿戴传感器系统,集成自动摄入监测器版本2 (AIM-2) 和距离传感器.
一种用于估计容器尺寸的新型模型,考虑到辐射透镜扭曲.
一个被动系统用于容器尺寸评估,没有用户交互.

主要成果:

消除对信托标记的需要.
摄像头系统 (AIM-2) 灵活地与食品相对定位.
精确的尺寸估计与低误差率:2.01%±4.10%的板块,2.75%±38.11%的碗高度,和4.58%±6.78%的碗直径.
该模型可以容纳非圆形板.

结论:

拟议的可穿戴传感器系统为容器尺寸估计提供了被动和用户友好的方法.
这种方法通过精确测量容器尺寸来提高自动食品份量大小估计.
该系统的灵活性和准确性代表了非交互式饮食评估工具的重大进步.

关键词:

饮食评估饮食评估食品成像技术食品成像技术食物份量是食物的一部分.食物的数量食物的数量部分大小估计部分大小估计.可以穿戴的传感器.穿戴式技术是一种可穿戴技术.

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