Detection of chewing and swallowing to estimate eating patterns and energy intake

检测咀嚼和吞咽以估计饮食模式和能量摄入

• 批准号: 7140644
• 负责人: EDWARD S SAZONOV
• 金额: $ 18.21万
• 依托单位: CLARKSON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7140644
• 关键词: artificial intelligence; behavior test; bioenergetics; bioengineering /biomedical engineering; biomedical automation; biomedical equipment development; biosensor device; biotechnology; caloric dietary content; calorimetry; clinical biomedical equipment; clinical research; computer program /software; disease /disorder prevention /control; human morbidity; human subject; mastication; noninvasive diagnosis; nutrient intake activity; nutrition related tag; obesity; portable biomedical equipment; quality of life; statistics /biometry; swallowing

DESCRIPTION (provided by applicant): The prevalence of obesity in developed countries is increasing at an alarming rate. Obesity contributes to an increased risk of heart disease, hypertension, diabetes, and some cancers and is now considered a risk factor for cardiovascular disease. The objective of this research is to investigate application of novel noninvasive devices and pattern recognition methods to perform studies of human food intake behavior and produce objective estimates of volumetric and caloric food intake that will be relevant for identifying effective measures to treat or prevent diseases like obesity. Such devices and methods could extend our understanding of causes of obesity, and the monitoring devices created in this study could be used for monitoring of obese patients and as a part of a therapy potentially improve quality of life and decrease the morbidity and mortality associated with obesity. The goal of this study is to design and perform a pilot investigation which will provide preliminary data that objective observations of mastication (chewing) and deglutition (swallowing) by a wearable, non-intrusive monitoring device can provide statistically reliable estimates of eating habits by providing objective measures of delution frequency, duration of mastication and identifying periods of food intake with sufficient sensitivity and specificity. The aims of the proposed research include design of the wearable sensors and associated signal processing methods; development of pattern recognition methodologies that will automatically detect instances of delution and mastication from sensor recordings; development of pattern recognition methods to automatically identify periods of food intake based on detected chewing and swallowing; and to validate these device and methodologies on a group of human subjects. Modern methods of computational intelligence such as artificial neural networks and fuzzy logic will be used along with statistical methods to achieve the highest 'accuracy of pattern recognition.

描述（由申请人提供）： 发达国家的肥胖患病率正在以惊人的速度增加。肥胖会增加患心脏病、高血压、糖尿病和某些癌症的风险，现在被认为是心血管疾病的危险因素。这项研究的目的是调查新型非侵入性设备和模式识别方法的应用，以对人类食物摄入行为进行研究，并对食物摄入量和热量进行客观估计，这将有助于确定治疗或预防肥胖等疾病的有效措施。此类设备和方法可以扩展我们对肥胖原因的理解，本研究中创建的监测设备可用于监测肥胖患者，并作为治疗的一部分，有可能改善生活质量并降低与肥胖相关的发病率和死亡率。本研究的目标是设计并进行一项试点调查，该调查将提供初步数据，通过可穿戴式非侵入式监测设备对咀嚼（咀嚼）和吞咽（吞咽）进行客观观察，可以通过提供统计上可靠的饮食习惯估计以足够的敏感性和特异性客观地衡量溶解频率、咀嚼持续时间和确定食物摄入时间。 拟议研究的目的包括可穿戴传感器的设计和相关的信号处理方法；开发模式识别方法，自动检测传感器记录中的溶解和咀嚼情况；开发模式识别方法，根据检测到的咀嚼和吞咽自动识别食物摄入周期；并在一组人类受试者身上验证这些设备和方法。人工神经网络和模糊逻辑等现代计算智能方法将与统计方法一起使用，以实现模式识别的最高“准确性”。

项目成果

Limited receptive area neural classifier for recognition of swallowing sounds using continuous wavelet transform.

使用连续小波变换识别吞咽声音的有限感受区神经分类器。

• 发表时间: 2007
• 作者: Makeyev, Oleksandr;Sazonov, Edward;Schuckers, Stephanie;Lopez;Melanson, Ed;Neuman, Michael
• 通讯作者: Neuman, Michael

Non-invasive monitoring of chewing and swallowing for objective quantification of ingestive behavior.

对咀嚼和吞咽进行无创监测，以客观量化摄入行为。

• 发表时间: 2008-05
• 影响因子: 3.2
• 作者: Sazonov, Edward;Schuckers, Stephanie;Lopez;Makeyev, Oleksandr;Sazonova, Nadezhda;Melanson, Edward L;Neuman, Michael
• 通讯作者: Neuman, Michael

Detection of food intake from swallowing sequences by supervised and unsupervised methods.

通过监督和非监督方法检测吞咽序列的食物摄入量。

• 发表时间: 2010-08
• 影响因子: 3.8
• 作者: Lopez;Makeyev, Oleksandr;Schuckers, Stephanie;Melanson, Edward L;Neuman, Michael R;Sazonov, Edward
• 通讯作者: Sazonov, Edward

Automatic detection of swallowing events by acoustical means for applications of monitoring of ingestive behavior.

通过声学手段自动检测吞咽事件，用于监测摄入行为。

• 发表时间: 2010-03
• 作者: Sazonov, Edward S;Makeyev, Oleksandr;Schuckers, Stephanie;Lopez;Melanson, Edward L;Neuman, Michael R
• 通讯作者: Neuman, Michael R

Toward objective monitoring of ingestive behavior in free-living population.

对自由生活人群的摄入行为进行客观监测。

• 发表时间: 2009-10
• 作者: Sazonov, Edward S;Schuckers, Stephanie A C;Lopez;Makeyev, Oleksandr;Melanson, Edward L;Neuman, Michael R;Hill, James O
• 通讯作者: Hill, James O