Challenges and Opportunities in Automated Detection of Eating Activity
Challenges and Opportunities in Automated Detection of Eating Activity
复制标题
自动检测饮食活动的挑战和机遇
DOI：
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复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
G. Abowd
中科院分区：
文献类型：
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作者：
Edison Thomaz;Irfan Essa;G. Abowd
受营养流行病学和食品日志应用的启发，计算研究人员多年来提出了许多自动化饮食监测的技术。虽然已经取得了进展，但一个真正实用的系统，可以自动识别人们在现实世界中吃什么仍然难以捉摸。进食检测是自动饮食监测（ADM）的基本要素，因为在确定摄入什么和摄入多少之前，需要自动识别一个人何时进食。此外，进食检测可以作为新型饮食自我监测实践的基础，如半自动化的食物journaling.This章讨论了自动进食检测的问题，并提出了各种实用的技术，在现实世界中检测进食活动。这些技术集中在三种传感模式上：使用可穿戴相机拍摄的第一人称图像，环境声音和身体惯性传感器[34，35，36，37]。本章首先分析了如何使用两种方法（人类计算和卷积神经网络）使用反映日常经历的第一人称图像来识别进食时刻。接下来，我们提出了一个分析，展示了如何识别与进食相关的某些声音，并用于推断进食活动。最后，我们介绍了一种方法，用于检测吃饭的时刻与身体惯性传感器放置在手腕上。
Motivated by applications in nutritional epidemiology and food journaling, computing researchers have proposed numerous techniques for automating dietary monitoring over the years. Although progress has been made, a truly practical system that can automatically recognize what people eat in real-world settings remains elusive. Eating detection is a foundational element of automated dietary monitoring (ADM) since automatically recognizing when a person is eating is required before identifying what and how much is being consumed. Additionally, eating detection can serve as the basis for new types of dietary self-monitoring practices such as semi-automated food journaling.This chapter discusses the problem of automated eating detection and presents a variety of practical techniques for detecting eating activities in real-world settings. These techniques center on three sensing modalities: first-person images taken with wearable cameras, ambient sounds, and on-body inertial sensors [34, 35, 36, 37]. The chapter begins with an analysis of how first-person images reflecting everyday experiences can be used to identify eating moments using two approaches: human computation and convolutional neural networks. Next, we present an analysis showing how certain sounds associated with eating can be recognized and used to infer eating activities. Finally, we introduce a method for detecting eating moments with on-body inertial sensors placed on the wrist.
影响因子：
4.2
作者：
Go, VLW;Nguyen, CTH;Lee, WNP
通讯作者：
Lee, WNP
DOI：
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发表时间：
1972-08
期刊：
Krankenpflege
影响因子：
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作者：
G. Siegmund
通讯作者：
G. Siegmund