Spectrogram-based audio classification of nutrition intake

Spectrogram-based audio classification of nutrition intake
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基于声谱图的营养摄入音频分类

DOI:
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发表时间:
2014
期刊:
Australian National Health Informatics Conference
影响因子:
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通讯作者:
M. Sarrafzadeh
M. Sarrafzadeh
中科院分区:
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文献类型:
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作者:
H. Kalantarian;N. Alshurafa;M. Pourhomayoun;Shruti Sarin;Tuan Le;M. Sarrafzadeh

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以不引人注目的、可穿戴的形式对食物摄入量进行声学监测,可以使个人能够监测自己的饮食模式、保持用餐时间的规律性并确保足够的水合水平,从而鼓励健康的饮食选择。在本文中,我们描述了一个系统,能够监测食物的摄入量,通过喉咙麦克风,分类数据的基础上被消耗的食物之间的几个类别,通过频谱分析,并提供用户反馈的形式移动的应用程序。我们能够将三明治吞咽、三明治咀嚼、水吞咽和无吞咽进行分类,F值为0.836。
Acoustic monitoring of food intake in an unobtrusive, wearable form-factor can encourage healthy dietary choices by enabling individuals to monitor their eating patterns, maintain regularity in their meal times, and ensure adequate hydration levels. In this paper, we describe a system capable of monitoring food intake by means of a throat microphone, classifying the data based on the food being consumed among several categories through spectrogram analysis, and providing user feedback in the form of mobile application. We are able to classify sandwich swallows, sandwich chewing, water swallows, and none, with an F-Measure of 0.836.
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