Automatic identification of the number of food items in a meal using clustering techniques based on the monitoring of swallowing and chewing.
Automatic identification of the number of food items in a meal using clustering techniques based on the monitoring of swallowing and chewing.
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DOI：
10.1016/j.bspc.2011.11.004
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发表时间：
2012-09-01
影响因子：
5.1
通讯作者：
Sazonov, Edward
中科院分区：
文献类型：
--
作者：
Lopez-Meyer, Paulo;Schuckers, Stephanie;Makeyev, Oleksandr;Fontana, Juan M.;Sazonov, Edward
关键词：
在肥胖和其他饮食失调的研究中，一顿饭中不同食物的摄入量是一个重要的临床问题。本文提出利用咀嚼和吞咽序列中包含的信息按食物类型进行膳食分割。从17名志愿者的实验中收集的数据使用两种不同的聚类技术进行分析。首先，使用无监督聚类技术亲和传播（AP）来自动识别一顿饭中的片段数量。其次，将无监督AP方法的性能与基于聚类层次聚类（AHC）的监督学习方法进行了比较。AP方法预测食品数量的准确率为90%，AHC方法的准确率为95%。实验结果表明，所提出的自动膳食分割模型可以作为自由生活条件下客观监测摄食行为的整体应用的一部分。
The number of distinct foods consumed in a meal is of significant clinical concern in the study of obesity and other eating disorders. This paper proposes the use of information contained in chewing and swallowing sequences for meal segmentation by food types. Data collected from experiments of 17 volunteers were analyzed using two different clustering techniques. First, an unsupervised clustering technique, Affinity Propagation (AP), was used to automatically identify the number of segments within a meal. Second, performance of the unsupervised AP method was compared to a supervised learning approach based on Agglomerative Hierarchical Clustering (AHC). While the AP method was able to obtain 90% accuracy in predicting the number of food items, the AHC achieved an accuracy >95%. Experimental results suggest that the proposed models of automatic meal segmentation may be utilized as part of an integral application for objective Monitoring of Ingestive Behavior in free living conditions.
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影响因子：
4.4
作者：
de Castro, JM
通讯作者：
de Castro, JM
影响因子：
3.8
作者：
Lopez-Meyer, Paulo;Makeyev, Oleksandr;Schuckers, Stephanie;Melanson, Edward L.;Neuman, Michael R.;Sazonov, Edward
通讯作者：
Sazonov, Edward
影响因子：
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通讯作者：
Walsh, B. Timothy
影响因子：
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作者：
Day, NE;McKeown, N;Bingham, S
通讯作者：
Bingham, S
影响因子：
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作者：
Sun M;Fernstrom JD;Jia W;Hackworth SA;Yao N;Li Y;Li C;Fernstrom MH;Sclabassi RJ
通讯作者：
Sclabassi RJ