E Silva Bruno Vieira Resende, Rad Milad Ghiasi, Cui Juan, McCabe Megan, Pan Kaiyue
Department of Computer Science and Engineering at University of Nebraska, Lincoln, USA.
Department of Complex Bio Systems at UNL, Lincoln, USA.
J Health Med Inform. 2018;9(2). doi: 10.4172/2157-7420.1000307. Epub 2018 Apr 6.
Personal diet management is key to fighting the obesity epidemic. Recent advances in smartphones and wearable sensor technologies have empowered automated food monitoring through food image processing and eating episode detection, with the goal to conquer drawbacks of traditional food journaling that is labour intensive, inaccurate, and low adherent. In this paper, we present a new interactive mobile system that enables automated food recognition and assessment based on user food images and provides dietary intervention while tracking users' dietary and physical activities. In addition to using techniques in computer vision and machine learning, one unique feature of this system is the realization of real-time energy balance monitoring through metabolic network simulation. As a proof of concept, we have demonstrated the use of this system through an Android application.
个人饮食管理是对抗肥胖流行的关键。智能手机和可穿戴传感器技术的最新进展通过食品图像处理和饮食事件检测实现了自动化食品监测，目的是克服传统食物记录法劳动强度大、不准确且依从性低的缺点。在本文中，我们提出了一种新的交互式移动系统，该系统能够基于用户的食物图像实现自动化食物识别和评估，并在跟踪用户饮食和身体活动的同时提供饮食干预。除了使用计算机视觉和机器学习技术外，该系统的一个独特功能是通过代谢网络模拟实现实时能量平衡监测。作为概念验证，我们通过一个安卓应用展示了该系统的使用。
